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Existing no-reference (NR) image quality assessment (IQA) metrics are still not convincing for evaluating the quality of the camera-captured images. Toward tackling this issue, we, in this article, establish a novel NR quality metric for quantifying the quality of the camera-captured images reliably. Since the image quality is hierarchically perceived from the low-level preliminary visual perception to the high-level semantic comprehension in the human brain, in our proposed metric, we characterize the image quality by exploiting both the low-level image properties and the high-level semantics of the image. Specifically, we extract a series of low-level features to characterize the fundamental image properties, including the brightness, saturation, contrast, noiseness, sharpness, and naturalness, which are highly indicative of the camera-captured image quality. Correspondingly, the high-level features are designed to characterize the semantics of the image. The low-level and high-level perceptual features play complementary roles in measuring the image quality. To infer the image quality, we employ the support vector regression (SVR) to map all the informative features to a single quality score. Thorough tests conducted on two standard camera-captured image databases demonstrate the effectiveness of the proposed quality metric in assessing the image quality and its superiority over the state-of-the-art NR quality metrics. The source code of the proposed metric for camera-captured images is released at https://github.com/YT2015?tab=repositories.

Context Radiomics is a field of science that aims to develop improved methods of medical image analysis by extracting a large number of quantitative features. New data have emerged on the successful application of radiomics and machine-learning techniques to the prediction of muscle-invasive bladder cancer (MIBC). Objective To systematically review the diagnostic performance of radiomic techniques in predicting MIBC. Evidence acquisition The literature search for relevant studies up to July 2020 was performed in the PubMed and EMBASE databases by two independent reviewers. The meta-analysis was inducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Inclusion criteria comprised studies that evaluated the diagnostic accuracy of radiomic models in predicting MIBC and used pathological examination as the reference standard. For bias assessment, Quality Assessment of Diagnostic Accuracy Studies-2 and Radiomic Quality Score were used. Weighted summary proportions were used to calculate pooled sensitivity and specificity. A linear mixed model was implemented to calculate the hierarchical summary receiver-operating characteristic (HSROC). Meta-regression analyses were performed to explore heterogeneity. Evidence synthesis Eight studies with a total of 860 patients were included. The summary estimates for sensitivity and specificity in predicting MIBC were 82% (95% confidence interval [CI]: 77–86%) and 81% (95% CI: 76–85%), respectively. The area under HSROC was 0.88. There were no relevant heterogeneity in diagnostic accuracy measures (I2 = 33% and 41% for sensitivity and specificity, respectively), which was confirmed by a subsequent meta-regression analysis. Conclusions Radiomics shows high diagnostic performance in predicting MIBC. Despite differences in approaches, radiomic models were relatively homogeneous in their diagnostic accuracy. With further improvements, radiomics has the potential to become a useful adjunct in clinical management of bladder cancer. Patient summary Rapidly evolving imaging analysis methods using artificial intelligence algorithms, called radiomics, show high diagnostic performance in predicting muscle-invasive bladder cancer.

Novel treatment modalities, such as non-invasive brain stimulation (NIBS), typically focus on patient groups that have failed multiple treatment interventions. Despite its promise, the clinical translation of NIBS in schizophrenia has been limited. One important obstacle to implementation is the inconsistent reporting of treatment resistance in the clinical trial literature contributing to heterogeneity in reported effects. In response, we develop a numerical approach to synthesize quality of assessment of Treatment-Resistant Schizophrenia (TRS) and apply this to studies investigating therapeutic response to NIBS in patients with schizophrenia. Literature search conducted through PubMed database identified 119 studies investigating Transcranial Magnetic Stimulation and Transcranial Electrical Stimulation in treating resistant schizophrenia symptoms. A quality score out of 11 was assigned to each study based on adherence to the international consensus guidelines for TRS developed by the Treatment Response and Resistance in Psychosis (TRRIP) group. Results revealed an overall paucity of studies with thorough assessment and/or reporting of TRS phenomenon, as evidenced by a mean quality score of 3.38/11 (SD: 1.01) for trials and 5.16/11 (SD: 1.57) for case reports, though this improved minimally since the publication of consensus criteria. Most studies considered treatment-resistance as a single dimensional construct by reporting resistance of a single symptom, and failed to establish treatment adherence, resistance time course and functional impairment. We conclude that the current NIBS literature in schizophrenia do not reflect its true effects on treatment-resistance. There is an urgent need to improve assessment and reporting standards of clinical trials that target TRS.

Many stereoscopic image retargeting (SIR) methods have been developed for automatically and intelligently resizing stereoscopic images and we cannot always rely on time-consuming subjective user studies to validate the performance of different SIR methods. It is therefore required to design reliable objective metrics for SIR quality evaluation. This paper extends our previous 2D aspect ratio similarity (ARS) metric to a stereo 3D version termed as StereoARS where the key idea is to investigate into retargeting inconsistency between the original stereo correspondences. Our proposed StereoARS operates via two stages: monocular quality estimation and binocular inconsistency detection. In the first stage, monocular quality estimation is performed by applying a modified ARS measure on the left and right views separately to quantify the quality degradation within each monocular view. In the second stage, binocular inconsistency detection is performed in both pixel-level and grid-level to characterize the influence of binocular rivalry and stereo visual discomfort on SIR quality. In addition, we also measure to what extent the original pixel visibility relation is preserved after SIR as another binocular quality factor. Finally, these monocular and binocular quality estimates are fused to produce an overall SIR quality score. Extensive experiments have demonstrated that StereoARS achieves better alignment with human subjective ratings than the existing metrics by a large margin.

Lung cancer's radiomic phenotype may potentially inform clinical decision-making with respect to radical radiotherapy. At present there are no validated biomarkers available for the individualisation of radical radiotherapy in lung cancer and the mortality rate of this disease remains the highest of all other solid tumours. MEDLINE was searched using the terms 'radiomics' and 'lung cancer' according to the Preferred Reporting Items for Systematic Reviews and Met-Analyses (PRISMA) guidance. Radiomics studies were defined as those manuscripts describing the extraction and analysis of at least 10 quantifiable imaging features. Only those studies assessing disease control, survival or toxicity outcomes for patients with lung cancer following radical radiotherapy ± chemotherapy were included. Study titles and abstracts were reviewed by two independent reviewers. The Radiomics Quality Score was applied to the full text of included papers. Of 244 returned results, 44 studies met the eligibility criteria for inclusion. End points frequently reported were local (17%), regional (17%) and distant control (31%), overall survival (79%) and pulmonary toxicity (4%). Imaging features strongly associated with clinical outcomes include texture features belonging to the subclasses Gray level run length matrix, Gray level co-occurrence matrix and kurtosis. The median cohort size for model development was 100 (15-645); in the 11 studies with external validation in a separate independent population, the median cohort size was 84 (21-295). The median number of imaging features extracted was 184 (10-6538). The median Radiomics Quality Score was 11% (0-47). Patient-reported outcomes were not incorporated within any studies identified. No studies externally validated a radiomics signature in a registered prospective study. Imaging-derived indices attained through radiomic analyses could equip thoracic oncologists with biomarkers for treatment response, patterns of failure, normal tissue toxicity and survival in lung cancer. Based on routine scans, their non-invasive nature and cost-effectiveness are major advantages over conventional pathological assessment. Improved tools are required for the appraisal of radiomics studies, as significant barriers to clinical implementation remain, such as standardisation of input scan data, quality of reporting and external validation of signatures in randomised, interventional clinical trials.

PurposeThe purpose is to assess the impact of clinical costing approaches on the quality of cost information in seven countries (Denmark, England, France, Germany, Ireland, the Netherlands and Portugal).Design/methodology/approachCosting practices in seven countries were analysed via questionnaires, interviews and relevant published material.FindingsAlthough clinical costing is intended to support a similar range of purposes, countries display considerable diversity in their approaches to costing in terms of the level of detail contained in regulatory guidance and the percentage of providers subject to such guidance for tariff setting. Guidance in all countries involves a mix of costing methods.Research limitations/implicationsThe authors propose a two-dimensional Materiality and Quality Score (2D MAQS) of costing systems that can support the complex trade-offs in managing the quality of cost information at both policy and provider level, and between financial and clinical concerns.Originality/valueThe authors explore the trade-offs between different dimensions of the quality (accuracy, decision relevance and standardization) and the cost of collecting and analysing cost information for disparate purposes.

Aims To determine the impact of a quality improvement (QI) initiative in the area of paediatric echocardiography (echo) in a low- to middle-income country (LMIC). Care for patients with congenital heart disease is challenging, especially in LMICs. Collaborative learning through QI projects is imperative to ensure improvement in delivery processes leading to better patient outcomes. Methods and results This QI initiative was taken by a team consisting of physicians and sonographers. Problems were identified, a key driver diagram (KDD) was created, and simple process re-engineering was done using interventions based on the KDD. Metrics (five process and one outcome) were assessed to determine the effectiveness of the QI project. The process metrics assessed were comprehensiveness of exam, timeliness of reporting, diagnostic accuracy and error, and sedation adverse event rates of transthoracic echocardiograms, while a novel comprehensive echo laboratory (lab) quality score was developed as an outcome metric. Data were collected quarterly and analysed in the post-implementation phase. Significant improvement was seen in comprehensive mean score (20.4–29.7), timeliness (40–95%), and diagnostic accuracy rate (91–100%), while a decrease was seen in the diagnostic error rate (7.5–3.5%) and the sedation adverse event rate (6.8–0%), pre- vs. post-implementation. The overall quality outcome score improved from 7 to 19 and the echo lab was able to achieve adequate quality. Conclusion This QI initiative produced improvement in all the processes, and the overall quality of the echo lab without any substantial increase in resources or cost.

Background To select the most complete, continuous, and accurate assembly for an organism of interest, comprehensive quality assessment of assemblies is necessary. We present a novel tool, called Evaluation of De Novo Assemblies (EvalDNA), which uses supervised machine learning for the quality scoring of genome assemblies and does not require an existing reference genome for accuracy assessment. Results EvalDNA calculates a list of quality metrics from an assembled sequence and applies a model created from supervised machine learning methods to integrate various metrics into a comprehensive quality score. A well-tested, accurate model for scoring mammalian genome sequences is provided as part of EvalDNA. This random forest regression model evaluates an assembled sequence based on continuity, completeness, and accuracy, and was able to explain 86% of the variation in reference-based quality scores within the testing data. EvalDNA was applied to human chromosome 14 assemblies from the GAGE study to rank genome assemblers and to compare EvalDNA to two other quality evaluation tools. In addition, EvalDNA was used to evaluate several genome assemblies of the Chinese hamster genome to help establish a better reference genome for the biopharmaceutical manufacturing community. EvalDNA was also used to assess more recent human assemblies from the QUAST-LG study completed in 2018, and its ability to score bacterial genomes was examined through application on bacterial assemblies from the GAGE-B study. Conclusions EvalDNA enables scientists to easily identify the best available genome assembly for their organism of interest without requiring a reference assembly. EvalDNA sets itself apart from other quality assessment tools by producing a quality score that enables direct comparison among assemblies from different species.

The problem of reproducing high dynamic range (HDR) images on electronic display and photography with restricted dynamic range has gained a lot of interest in the consumer electronics community. There exist various approaches to this issue, e.g., tone mapping operators (TMOs) and multi-exposure fusion algorithms (MEFs). Many existing image quality assessment (IQA) methods have been proposed to compare images of quality degradation generated by TMOs/MEFs. Although promising performances have been achieved, they seldom consider local specific artifacts difference (i.e., abnormal exposure and color cast) related with the TMOs/MEFs. To address this limitation, this paper proposes a Blind Quality Evaluator of Tone-Mapped HDR and Multi-Exposure Fused Images (BQE-TM/MEFI). First, two purpose-designed segment models are utilized to distinguish well-exposedness dense patches (WEDPes) and non-WEDPes, color cast patches (CCPes) and non-CCPes respectively. Second, multiple quality-perception features are extracted to measure local artifacts: 1) structure and sharpness features from WEDPes, 2) saturation features from non-CCPes, and 3) edge structure features. Then, three new low-complexity regional features (over-exposure ratio, entropy and color confidence index) are calculated based on over-exposure segmentation model. Finally, all extracted features are aggregated into a machine-learning regression model to pool a quality score. The simplicity and good performance of the proposed method makes it suitable for electronic displays and other consumer electronics.

Background: The internet is a broadly preferred source of information both by patients and medical professionals. YouTube™ is a significant information source that may be a useful tool to inform the public, medical students, and residents, and may improve the learning experience if used adequately. In this study, we aimed to estimate the quality and accuracy of videos regarding Transoral Endoscopic Thyroidectomy Vestibular Approach (TOETVA) aired on YouTube, which is the most popular video platform of the online world. Materials and Methods: We evaluated the first 50 videos, returned by the YouTube research engine, in reply to the "TOETVA" keyword. The popularity of the videos was assessed using the video power index (VPI). The educational quality, accuracy, and transparency of the content regarding TOETVA were estimated by using the DISCERN questionnaire score (DISCERNqs), Journal of American Medical Association benchmark criteria (JAMABC), and global quality score (GQSc). The technical quality was ranked through TOETVA Scoring System (TOETVA-SS) by a TOETVA practicioning endocrine surgeon. Results: The content of the videos were about surgical technique with a rate of 68%. According to sources, videos uploaded by physicians had significantly higher DISCERNqs, JAMABC, GQSc, and TOETVA-SS scores. Unlike, videos uploaded by physicians had a lower VPI than videos uploaded by nonmedical sources. The videos of surgical technique had significantly higher DISCERNqs, JAMABC, GQSc, and TOETVA-SS scores. Surgical technique videos also had higher VPI scores than "information about disease or surgery" videos. Also, negative correlations were found between the VPI (popularity index) and educational value (GQSc), transparency (JAMABC), and technical quality (TOETVA-SS) scores. Conclusions: The data acquired from YouTube videos regarding TOETVA is of below expected quality and reliability. Nevertheless, the educative potential of the online video platform, YouTube, cannot be underestimated.

Objectives The addition of green spaces (GS) in cities is perceived as an efficient solution to combat climate change and biodiversity loss while also improving human health. Quantitative health impact assessment (QHIA) is a powerful tool to assess the health benefits of GS and support policy-making decisions. In France, a preliminary analysis of the literature led to the decision of developing guidance for QHIA applied to GS and mortality. This paper focuses on the choice of exposure-response functions (ERF) for those QHIA. Study design Literature review and analysis of the key steps of QHIA. Methods Articles providing ERF for all-cause, cardiovascular and respiratory mortality in relation to GS were identified through a literature review and ranked based on a quality score. ERF from the articles with the highest scores was pooled in meta-analyses. Results In total, 13 ERF were selected for all-cause mortality, 10 for cardiovascular mortality and 5 for respiratory mortality. Meta-risk for a 0.1 increase in the normalised differential vegetation index were, 0.96 (95% confidence interval [CI] 0.94; 0.97), 0.98 (95% CI 0.96; 0.99) and 0.97 (95% CI 0.92; 1.02) for all-cause, cardiovascular and respiratory mortality, respectively. Conclusions While current knowledge makes it possible to use QHIA on GS and mortality, interdisciplinary research is still needed to clarify the shape of the relationship and its temporality and to assess exposure in a meaningful way for decision-making.

INTRODUCTION To improve compliance with voiding diaries in children with primary monosymptomatic nocturnal enuresis (PMNE), a new modified 3-day weekend frequency-volume chart (FVC) was designed, and the compliance and validity of this modified FVC was evaluated by comparing with the International Children's Continence Society (ICCS) recommended voiding diary. METHODS A total of 1200 patients with PMNE were enrolled in the study from 13 centers in China and were randomly assigned to record this modified FVC or the ICCS-recommended voiding diary. The primary outcome measure was the compliance, assessed by comparing the completing index and the quality score of diaries between two groups. The secondary outcome measure was the validity, evaluated by comparing the constituent of subtypes, micturition parameters and response rate to desmopressin. RESULTS Among the 1200 participants enrolled in the study, 447 patients completed the ICCS-recommended voiding diary and 469 completed the modified diary. The diurnal completing index and the quality score of the modified FVC group were better than those of the ICCS group. In addition, there was no significant difference between these two groups in the subtype classification, or in the response rate to desmopressin. CONCLUSIONS The modified FVC could be applied to obtain the voiding characteristics of children with PMNE as the ICCS-recommended voiding diary does and offers a reasonable and better choice for children with PMNE from the unselected population in the future.

Aim To perform a systematic review of available mHealth apps for menstrual cycle monitoring in Brazil. Methods A search for menstrual cycle mHealth apps from the Google Play Store and AppStore in Brazil was performed by two independent reviewers on October 2020, and the quality of eligible mHealth apps was assessed using the Mobile App Rating Scale (MARS). Results Our review identified 2400 potentially relevant mHealth apps, of which 56 were eligible for inclusion. The majority of the apps offered tools to track menstruation symptoms (63%) and educational content for users (32%). The mean ( ±SD) MARS app quality score for the 28 evaluated apps in Android was 3.5 ± 0.6 on a 0-5 scale. For the 28 evaluated apps in iOS, the mean app quality score was 3.8 ± 0.4. Most of the included apps, for both systems, scored average for credibility, user interface, and engagement. Conclusion The majority of available tools in Brazil are of moderate quality and limited functionality for menstrual cycle monitoring. This study highlights the top three mHealth apps available on each online store for individuals seeking menstrual cycle monitoring options.

In order to integrate genomic medicine into routine patient care and stratify personal risk, it is increasingly important to record family history (FH) information in general/family practice records. This is true for classic genetic disease as well as multifactorial conditions. Research suggests that FH recording is currently inadequate.To provide an up-to-date analysis of the frequency, quality, and accuracy of FH recording in UK general/family practice.An exploratory study, based at St Leonard's Practice, Exeter-a suburban UK general/family practice. Selected adult patients registered for over 1 year were contacted by post and asked to complete a written FH questionnaire. The reported information was compared with the patients' electronic medical record (EMR). Each EMR was assessed for its frequency (how often information was recorded), quality (the level of detail included), and accuracy (how closely the information matched the patient report) of FH recording.Two hundred and forty-one patients were approached, 65 (27.0%) responded and 62 (25.7%) were eligible to participate. Forty-three (69.4%) EMRs contained FH information. The most commonly recorded conditions were bowel cancer, breast cancer, diabetes, and heart disease. The mean quality score was 3.64 (out of 5). There was little negative recording. 83.2% of patient-reported FH information was inaccurately recorded or missing from the EMRs.FH information in general/family practice records should be better prepared for the genomic era. Whilst some conditions are well recorded, there is a need for more frequent, higher quality recording with greater accuracy, especially for multifactorial conditions.Taking a family history (FH) of disease can be a quick, cost-effective way of gathering genetic information. Genetic medicine is beginning to transform healthcare, so it is important to gather FH information. General practitioners, also known as family physicians, are in the best position to gather FH information as they regularly see multiple family members. Research suggests that FH recording in general/family practice is not yet good enough. This study aimed to find the areas for improvement by measuring the frequency, quality, and accuracy of FH recording. This study looked at 62 patients’ records in one UK general practice. Patients were asked to give up-to-date FH information in a questionnaire which was compared with their record. The study found that some conditions were often recorded. The most commonly recorded condition was heart disease. The conditions that are more likely to reflect the family environment, such as depression, were less frequently recorded. Recordings often included the side of the family the condition affected. Recordings rarely included the age that the relative was affected. The information was not very accurate, as most of the information from patient questionnaires was missing from the records. Research should now focus on how to improve recording.

Aim: To evaluate the quality of YouTube™ videos on bladder pain syndrome (BPS) and to investigate whether they can be used as a reliable source of information. Methods: The search term "bladder pain syndrome" was used on YouTubeTM platform. The first 100 videos were selected. Patient Education Materials Assessment Tool for audio-visual content (PEMAT A/V), Global Quality Score (GQS), Misinformation tool, and DISCERN score were used to assess videos' quality content. Pearson's test was used to assess potential correlations between variables. Results: Seventy-nine videos were suitable for the analyses. The median PEMAT A/V Understandability score and PEMAT A/V Actionability score were 66.7% (interquartile range [IQR]: 46.2-100.0) and 75.0% (IQR: 37.5-100.0), respectively. According to GQS, 26 (32.9%), 32 (40.5%), 3 (3.8%), 15 (19.0%), and 3 (3.8%) videos were excellent, good, moderate, generally poor, and poor, respectively. According to Misinformation tool, of all videos, 81% (n = 64), 6.3% (n = 5), 5.1% (n = 4), 5.1% (n = 4), 2.5% (n = 2) had respectively no, very little, moderate, high, and extreme misinformation. The overall median DISCERN score ranged from 5.0 (IQR: 2.0-5.0) to 5.0 (IQR: 5.0-5.0). A positive statistically significant correlation was found between video length and PEMAT A/V Understandability (r = 0.27, p = 0.01), video length and PEMAT A/V Actionability (r = .26, p = 0.02), and video length and DISCERN Question 16 (r = 0.28, p = 0.01). Conclusions: Nowaday, the overall quality of YouTubeTM videos on BPS have been evaluated good according to PEMAT A/V, GQS, Misinformation tool, and DISCERN score. It is possible to assume that YouTubeTM may be considered as a reliable source of information on BPS.

Background With the improvement of therapeutic strategies from cytotoxic chemotherapy to immunotherapy, the possibility of achieving timely intervention for lung cancer has dramatically increased. This study aimed to systematically evaluate the reporting quality of randomized controlled trials (RCT) on immunotherapy in lung cancer. Methods The RCTs evaluating the efficacy of immunotherapy in lung cancer published up to 2021 were searched and collected from PUBMED and EMBASE by two investigators. The 2010 Consolidated Standards for Test Reports (CONSORT) statement‐based 28‐point overall quality score (OQS) and the 2001 CONSORT statement‐based 19‐point OQS was utilized for assessing the overall quality of each report. Results One hundred and fifty‐two related RCTs were retrieved in this study, including 81,931 patients. The average OQS in 2010 was 17.89 (range, 7.5–24.5). Overall, studies have sufficiently reported the eligibility criteria (143/152; 94.07%), described the scientific background (150/152; 98.7%) and discussed interventions (147/152; 96.7%). However, the RCTs did not consistently report the changes to trial after commencement (48/152; 31.6%), allocation, enrollment and assignment personnel (34/152; 22.4%), blinding (48/152; 31.6%), or randomization method (58/152; 38.2%). Conclusions The overall reporting quality of RCTs on immunotherapy in lung cancer was found to be unsatisfactory despite the fact that the CONSORT statement was issued more than a decade ago. Furthermore, there was virtual selectivity and heterogeneity in reporting some key issues in these trials. This is the first study to enlighten lung cancer researchers especially focusing on immunotherapy, and also to remind editors and peer reviewers to strengthen their due diligence., The 2010 Consolidated Standards for Test Reports (CONSORT) statement‐based 28‐point overall quality score (OQS) and the 2001 CONSORT statement‐based 19‐point OQS was utilized to assess the quality of randomized controlled trials (RCTs) on immunotherapy in lung cancer published in PUBMED and EMBASE, demonstrating an unsatisfactory overall reporting quality, enlightening lung cancer researchers to pay more attention to CONSORT projects when designing and reporting trials, and bringing up the necessity for editors and peer reviewers to be more scrutinizing and diligent for RCTs on immunotherapy in lung cancer.

Searching for information on the Internet, especially YouTubeTM, is gaining popularity for cancer survivors. Based on the topic of online health information, the importance of studies using YouTube data for various cancer types and treatment methods has increased. This study aims to investigate the quality, reliability, and accuracy of YouTube videos on cancer rehabilitation (CR). YouTube search was performed on February 26th, 2021, with two keyword sets: “cancer rehabilitation” and “oncology rehabilitation.” The modified DISCERN, the Journal of the American Medical Association (JAMA) scoring system, and the Global Quality Score (GQS) were used to evaluate the quality and reliability of the videos. The features of each video such as the number of likes, dislikes, and views, upload date, duration, like ratio, and the uploader profile were also collected. Fifty-three of the first 200 videos shown in the search results met the criteria. Most of the videos were low quality. The most common uploader profile was academic institute/university hospital. The three most common subjects in the videos were CR definition, physical therapy and occupational therapy, and patient experiences. The mean modified DISCERN, JAMA, and GQS scores were 2.14, 2.03, and 2.78, respectively. Higher quality videos had longer duration, greater number of views, and better reliability scores. The results showed that most of the rated videos were of low-quality and didn’t provide sufficient information on the topic discussed. Higher-quality and more accurate YouTube videos are needed to increase awareness of CR. For cancer survivors, CR-related YouTube video content often provides information of low reliability. In this context, it is necessary to focus on the production of video content that includes clinical guides, references, and are based on clinical-based practices.

Objectives: We aim was to evaluate the quality and reliability of the information on knee arthroplasty available on YouTube in Turkish. Methods: A systematic search was conducted using the term “diz protezi” (knee prosthesis) on 1 June 2020.Videos were filtered based on their degree of relevance alone. Videos that were not in Turkish, not on knee prosthesis or without audio and/or image were excluded. Copied videos were evaluated as a single video. The first 50 videos that came up in the search were included in the study. Video quality was scored using Global Quality Score (GQS). To assess reliability, modified DISCERN scale was used. Results: The mean view count per video was 31.533 ± 100.921 and the total view count was 1.576.633. The mean duration per video was 337 ± 475 seconds. The median number of likes per video was 13 (0-426). The median number of dislikes per video was 2.5 (0-83). The mean GQS of the videos was 3.25 ± 0.9. When the reliability of the sources was evaluated using DISCERN, the mean score of the videos was 2.18 ± 1.2. It is striking that all videos were prepared by an orthopedic surgeon. Of the medical doctors preparing the resources, 44% had academic titles. Conclusions: It was found that Turkish resources on arthroplasty on YouTube are promising in terms of quality. Content creators must make effort to increase their reliability according to DISCERN.

The commercial light field camera is able to capture four-dimensional Light Field Image (LFI), which can be visualized to LFI contents on 2D displays by means of the Pseudo Video (PV) or the Refocused Images (RIs) generated with the refocusing function of LFI. However, the quality degradation of LFI will affect user’s visual experience of LFI contents. Hence, it is crucial to develop an effective LFI quality assessment method to monitor the LFI quality. Most existing subjective databases of LFI use PV and RIs visualization techniques to assess the quality of LFI. Therefore, as the way of presenting LFI on 2D display, PV and RIs are closely related to the subjective perception of LFI by human eyes. Based on these two visualization techniques, this article proposes a novel PV and RIs based blind LFI quality assessment method, in which the feature extraction is divided into two parts. In the first part, the PV’s structure, motion and disparity information are extracted with multi-scale and multi-directional Shearlet transform. In the other part, the spatial structure, depth and semantic information of the RIs are obtained. Finally, support vector regression is used to nonlinear map the perceptual features to quality score of LFI. The experimental results on four LFI databases show that the proposed method has better correlation with human visual perception, compared with the classical 2D image quality assessment methods as well as the state-of-the-art LFI quality assessment methods.

Face quality assessment has grown into a necessary pre-requisite for better performance of the face recognition (FR) algorithm pipeline. In this work, we proposed a novel face quality assessment algorithm for face recognition algorithms. We named it simplified face quality assessment (SFQA) for its simple provision to be used in accompaniment with any FR algorithm. We first proposed a hashing based deep learning model for the prediction of face quality from the features of the corresponding FR algorithm. The last layer of the deep hash net gives binary bits as output which is then converted to the decimal value to get the face quality score (FQS) ranging between 0 and 100. The mutual quality of the probe and gallery images are mathematically clubbed to get the Face Quality Confidence Score (FQCS). We have experimentally shown the effects of FQCS on the recognition algorithm. We trained the prediction model using the FR algorithm for the quality estimation on the face images from CAS-PEAL, LFW, and QDF database. The performance of SFQA is found to outperform the state-of-the-art methods, as discussed in the paper.

The aim of this study was to characterize the educational quality and reliability of YouTube videos related to low back pain (LBP) as well as to identify factors associated with the overall video quality. A review of YouTube was performed using two separate search strings. Video-specific characteristics were analyzed for the first 50 videos of each string. Seventy-seven eligible videos were identified as a result. The mean Journal of the American Medical Association score was 2.25 ± 1.09 (range: 0-4) out of 4. The mean Global Quality Score (GQS) score was 2.29 ± 1.37 (range: 1-4) out of 5. The mean LBP score (LPS) score was 3.83 ± 2.23 (range: 0-11) out of 15. Video power index was a predictor of GQS score (β = 55.78, p = 0.048), whereas the number of likes (β = -2.49, p = 0.047) and view ratio (β = -55.62, p = 0.049) were associated with lower quality scores. Days since initial upload (β = 0.32, p = 0.042) as well as like ratio (β = 0.37, p = 0.019) were independent predictors of higher LPS scores. The results of this study suggest that the overall reliability and educational quality of videos uploaded to YouTube concerning LBP are unsatisfactory. More popular videos demonstrated poorer educational quality than their less popular counterparts. As the prevalence of LBP rises, more accurate and thorough educational videos are necessary to ensure accurate information is available to patients.

Purpose Advanced medical image analytics is increasingly used to predict clinical outcome in patients diagnosed with gastrointestinal tumors. This review provides an overview on the value of radiomics in predicting response to treatment in patients with gastrointestinal tumors. Methods A systematic review was conducted, according to PRISMA guidelines. The protocol was prospectively registered (PROSPERO: CRD42019128408). PubMed, Embase, and Cochrane databases were searched. Original studies reporting on the value of radiomics in predicting response to treatment in patients with a gastrointestinal tumor were included. A narrative synthesis of results was conducted. Results were stratified by tumor type. Quality assessment of included studies was performed, according to the radiomics quality score. Results The comprehensive literature search identified 1360 unique studies, of which 60 articles were included for analysis. In 37 studies, radiomics models and individual radiomic features showed good predictive performance for response to treatment (area under the curve or accuracy > 0.75). Various strategies to construct predictive models were used. Internal validation of predictive models was often performed, while the majority of studies lacked external validation. None of the studies reported predictive models implemented in clinical practice. Conclusion Radiomics is increasingly used to predict response to treatment in patients suffering from gastrointestinal cancer. This review demonstrates its great potential to help predict response to treatment and improve patient selection and early adjustment of treatment strategy in a non-invasive manner.

Objective quality assessment aims towards evaluating the perceptual quality of a signal using a machine-based algorithm. Due to different challenges involved in the subjective evaluation of speech quality, it is necessary to develop objective measures. The goal of any non-intrusive quality assessment metric for noise-suppressed speech is to assess the quality of a noise-suppressed signal in the absence of any clean reference signal. As per the ITU-T P.835 recommendations, the quality assessment of noise-suppressed speech involves predicting three quality scores, namely, signal quality, background quality, and overall quality score, and hence, considered in this study. In recent literature, the non-intrusive quality assessment problem is presented as a regression problem, in which the mapping between a set of acoustic features and corresponding quality scores is found using a perceptual model. Recently, we proposed the use of Deep Autoencoder (DAE) features and Subband Autoencoder (SBAE) features for acoustic representation and an Artificial Neural Network (ANN) as a regression model. DAE and SBAE are variants of autoencoder architecture that have bottleneck structure in the hidden layers. Such architecture represents the class of generalized nonlinear Principal Component Analysis (PCA) that guarantees reconstruction of the input features with arbitrary accuracy. Both the features (DAE and SBAE) are extracted using unsupervised deep learning architectures, and they demonstrated better performance than the state-of-the-art spectral feature set, namely, Mel Filterbank Energies (FBEs). In this paper, we present more detailed analysis of previously proposed features, i.e., DAE and SBAE features, and analyze the usefulness of these features in predicting signal as well as background quality scores in addition to the overall quality score. We compare the performance of all the three features with each other as well as with current ITU-T P.563 metric for non-intrusive speech quality assessment. The results of our experiments performed on NOIZEUS database suggest that DAE and SBAE features perform relatively better than the FBEs while predicting signal and overall quality. On the other hand, FBE features perform slightly better than the DAE and SBAE features in predicting the background quality. Moreover, another major contribution of this paper is that we employ an ANN to predict all the three quality scores simultaneously, and present the results. It was observed that using this approach, it is possible to predict all the three scores simultaneously with similar accuracy as that of predicting them individually.

Introduction/objectives: A progressively growing number of rheumatologists have integrated musculoskeletal ultrasound (MSUS) as a prized tool in their daily clinical practice over the past two decades. Lately, YouTube is often used by healthcare professionals as an educational tool. This study aimed to analyze the quality of educational information available on YouTube pertaining to MSUS. Method: We performed a search using the keyword “musculoskeletal ultrasound” on YouTube in January 2021. Of the first 200 videos screened, 147 met the inclusion criteria. The quality and reliability of the videos were evaluated using the global quality score (GQS) and modified DISCERN score, and their popularity was assessed using the Video Power Index (VPI). Results: Of the 147 videos evaluated, 58 (39.5%) were of high quality, 30 (20.4%) were of moderate quality, while 59 (40.1%) were of low quality. The modified DISCERN score and the duration of the videos were significantly higher in the high-quality videos than the moderate- and low-quality videos (p < 0.001 for all). The median number of views per day, likes, comments, and the popularity of the videos assessed with VPI were significantly higher in the high- and moderate-quality group compared to the low-quality videos (p < 0.001, p < 0.001, p = 0.007, and p < 0.001, respectively). Conclusion: The quality of YouTube videos as an educational source on MSUS is unsatisfactory. Professional organizations and physicians should consider creating more high-quality MSUS videos. YouTube should consider filtering out poor-quality videos in collaboration with experts in the field.Key Points• Although rheumatologists are increasingly using ultrasound as an extension of their exam, accessing musculoskeletal ultrasound training is still facing some challenges.• YouTube is commonly used as an educational source by medical students and healthcare professionals.• Approximately 60% of the videos related to musculoskeletal ultrasound on YouTube revealed high and moderate quality, while the remaining 40% were of low quality and not suitable for medical education.• A filtering mechanism is required to improve the quality of YouTube content on MSUS

Omnidirectional video quality assessment (OVQA) helps to evaluate the viewers’ visual experience and promotes the development of omnidirectional video. The perceived quality of omnidirectional video is affected not only by the video content and distortion, but also by the viewing directions of viewer’s preference. At present, there are some quality assessment methods for omnidirectional video, but most of them are full-reference (FR). Compared with the FR method, the no-reference (NR) method becomes more difficult due to the lack of the reference video. In this paper, a NR OVQA based on generative adversarial networks (GAN) is proposed, which is composed of the reference video generator and the quality score predictor. Generally, a reference image/video is distorted by some distortion types, and each distortion type has some distortion levels. To the best of our knowledge, there are some NR methods using GAN to generate the reference images/videos for quality assessment. In these methods, the reference images/videos is generated by GAN when the distorted images/videos, which are from a distortion type but with different distortion level, are input into the GAN. In order to achieve an accurate quality assessment, the generated reference images/videos, which are from a distortion type but with different distortion level, are expected to have as similar quality as possible with each other. However, the distorted images/videos are independent for GAN, and the GAN will generate a little different reference images/videos for these distorted images/videos. This issue is not considered in the existing GAN-based methods. To solve this issue, we introduced a level loss in OVQA. For the quality score predictor, as a further contribution of this paper, the viewing direction of the omnidirectional video is incorporated to guide the quality and weight regression. The publicly available dataset is used to evaluate the proposed method. The experimental results indicate the effectiveness of the proposed method.

The online question answering (QA) community has been popular in recent years. In this paper, we focus on the online health question answering (HQA) community. The HQA community provides a platform for health consumers to inquire about health information. There are two ways to use this platform. One is to post a question and wait for answers to be provided by authenticated doctors. The other is to search for relevant questions with answers. For the latter, health consumers may prefer an accepted answer marked by the previous health consumer. However, there is a large proportion of questions without an accepted answer and it is inconvenient for people who want to search for relevant questions. To address this issue, we aim to select high-quality answers from the answers without marked accepted answers. We propose a deep learning approach to achieve this goal. To train the model for the prediction of answer quality, we first view the accepted answer as the positive answer and propose a method to label the negative answer. Next, we capture the semantic information on the question and the answer by the deep learning structure. We then combine the information to predict the quality score of the answer. We collect data from one of the biggest Chinese HQA community and divide them into groups by the medical departments for detailed analysis. Finally, we conduct experiments to show the effectiveness of categorization and the labeling method. The results show that our approach outperforms other studies and we further research into the differences among the results of different categories.

Objectives: Cigarette smoking continues to be the leading cause of preventable morbidity and mortality in the United States. Tobacco related mortality has promoted a massive effort to understand and enhance smoking cessation efforts. In this study, we examine the role of different factors on intentions to quit smoking. Methods: Data is taken from Health Information National Trends Survey (HINTS) 2012. A total of 1745 national representative samples of U.S adults, meeting our research conditions, were included in this study. Results: Multivariate statistical analysis methods were used which showed that employed participants were 6 times more likely to have intentions to quit than participants with other occupational statuses were. Participants who received support sometimes from health professionals were 9 times more likely to have intention to quit smoking as compared to those who never received support from health professionals. In addition, race (Hispanic), and age group (35-39 years) are significantly associated with intentions to quit smoking. Perceived personal risk of cancer, perceived compared risk of cancer, and family history of cancer were not significantly associated with intentions to quit smoking. Conclusion: Our study suggests that age, race, occupational status, and help from health professionals are viable intervention targets for smoking cessation interventions. As a key role can be played by health professionals in smoking cessation interventions, future work should evaluate the extent to which health professionals can play a role in smoking cessation intervention. Smokers should be encouraged to maintain smoke free environments in their homes and offices, by health care providers leading to the protection of non-smokers, lesser convenience for smoking, decreased cigarette consumption, and smoking cues over time.

The internet is widely used by the public to look for health-related information. The quality of information about shin guard characteristics and protective benefits is lacking. The objectives of this study are the folowing: (1) to summarise currently available knowledge on shin guards. (2) To assess the quality of websites presenting information pertinent to shin guards by using previously validated scoring systems. (3) To develop a novel scoring system to assess the accuracy of the content available online on shin guards. First, scientific knowledge about shin guards was developed by searching the scientific databases. Second, we identified eligible websites containing information about shin guard by searching the top 3 English search engines (Google, Yahoo! and Bing). Finally, to evaluate the websites, we searched peer-reviewed articles to identify appropriate scoring systems to assess the quality of health information on the internet. 25 Web sites were included; the mean overall score was 17.4 out of 35 (49.7%). The average quality score was 5.3 out of 15 (35.3%) and the average reliability score was 12.2 out of 20 (61%). Overall, most of the websites retrieved are of poor quality, with none of the websites’ total score reaching the threshold to be included in the “Excellent Category” and only one website was qualified to be added to the “very good category”. Our study suggests that there is paucity of websites available providing reliable and accurate information about shin guards.

Objective The quality of patient information relating to intermittent claudication (IC) and peripheral arterial disease (PAD) on the World Wide Web was assessed. Methods The quality of websites and YouTube videos was assessed using the search terms “intermittent claudication” and “peripheral arterial disease”. The first 50 hits screened for each search term from the three largest search engines by market share, and the first 20 videos from YouTube were screened. Website quality was scored using the University of Michigan Consumer Health Website tool (maximum score 80). Readability was calculated using the Flesch Reading Ease (FRE) score (maximum score 100). Videos were classified by content and upload source. Video reliability was assessed using the JAMA benchmark criteria. Video educational content was assessed using the Global Quality Score (GQS). Subjective content assessment was undertaken. Results Seventy-six websites were analysed. The majority of websites for both IC (51.7%) and PAD (72.3%) were rated as weak. The median Michigan score for IC (27; interquartile range [IQR] 15, 32.5) was lower that the score for PAD (31; IQR 25.5, 38.8; p = .030). The majority of websites for both IC (69%) and PAD (68.1%) were rated as requiring an above average reading level. The overall median FRE score was 55.9 (IQR 46.6, 60.6) for IC and 55.3 (IQR 44.6, 59.3) for PAD. Twenty-two videos were analysed. Of the 14 videos evaluated as part of the PAD search, the median JAMA score was 2 (2 – 3), the median GQS score was 3 (3 – 3) and the evaluation of content score was 8.5 (7.25 – 11.5). The equivalent scores for the IC search were 2 (2 – 2), 3 (3 – 4), and 5.5 (5 – 8). Conclusion The educational quality and reliability of information both in written and video form on the internet is low. Attention needs to focus on improving the quality of all forms of information delivery to allow proper advocacy for patients.

Aim: The aim of the study is to evaluate the quality and reliability of videos about Achilles tendon ruptures on YouTube.Material and Methods: The first 50 videos were included in the study by typing the keyword 'achilles tendon rupture' in the YouTube search tab. The videos were analyzed by two orthopedic surgeons. All videos were analyzed by length, number of views, number of likes, dislikes and source of the video. Global Quality score (score range: 1-5), Journal of the American Medical Association (0-4) and DISCERN (15-75) scoring systems were used to evaluate the quality of the videos. The data obtained were analyzed statistically according to these scoring systems. The Video Power Index (VPI) was used to evaluate the popularity of videos.Results: In this study, 50 videos were evaluated. According to the DISCERN score, five (10%) videos were excellent, ten (20%) videos were good, eight (16%) videos were medium, ten (20%) videos were poor and seventeen (34%) videos were observed to be very poor. Average DISCERN, JAMA and GQS of all videos evaluated were 38.85 ± 16.2 (16.5-66), 2.52 ± 0.64 (2-4), and 2.47 ± 1.34 (1-5), respectively. Avarage like ratio was 91.68 ± 14.79, view ratio was 59.99 ± 117 and Video Power Index was 56.98 ± 11.66 (0.01-736.79). There was a weak correlation between Video Power Index, DISCERN and Global Quality Scores, but not with the Journal of the American Medical Association score. (P = 0.22, 0.030, 0.940, cc = 0.330, 0.313, 0.11, respectively). Conclusion: The quality of YouTube videos related to Achilles tendon rupture is poor. Physicians can take online patient education to higher levels by highlighting less discussed topics in these videos.

OBJECTIVE To identify pelvic floor muscle therapy mobile health applications (apps) targeting women with urinary incontinence (UI), and evaluate them in a standardized fashion. METHODS A systematic search of English language apps on the Canadian App Store (iOS) and Google Play (Android) Store was performed. Eligible apps were evaluated independently by 5 reviewers using the validated Mobile App Rating Scale (MARS) tool. Descriptive characteristics were summarized and MARS subscale and overall quality scores werereported. RESULTS Of 139 mobile health apps identified, 20 unique apps were included for full review, of which there were 7 iOS only apps, 6 Android only apps, and 7 apps available in both stores. At the time of analysis, most apps had been updated within the last year (60%). Only 1 app had been trialed and verified by evidence in scientific literature. The majority of apps were free to download (80%). The median (interquartile range) MARS overall quality score was 3.7 (0.8) on a 0-5 scale, ranging from 2.7 to 4.1. The highest-rated subscale was “functionality” with a median score of 4.1 (0.6); the lowest-rated was “information” with a median score of 3.4 (0.6). The median MARS subjective quality score was 2.9 (1.0). CONCLUSION There are both free and paid apps available on-line that deliver pelvic floor muscle therapy programs. Evaluation using the MARS tool identified that many apps are not of high quality, and only 1 was evidence-based and has been trialed clinically. This knowledge is relevant to the choice of apps by both patients and caregivers.

No reference image quality assessment (NR-IQA) has received considerable importance in the last decade due to a rise in the use of multimedia content in our daily lives. Due to limitations in technology, multiple distortions may be introduced in the images that need to be assessed. Recently feature selection has shown promising results for single distorted NR-IQA and their effectiveness on multiple distorted images still need to be addressed. In this paper, impact of feature level fusion and feature selection on multiple distorted image quality assessment is presented. To this end features are extracted from multiple distorted images using six NR-IQA techniques (BLIINDS-II, BRISQUE, CurveletQA, DIIVINE, GM-LOG, SSEQ) that extract features in different (discrete cosine transform, spatial, curvelet transform, wavelet transform, spatial and gradient, spatial and spectral) domains. The extracted features from different domains are fused to generate a single feature vector. All combinations of feature-level fusion from six different techniques have been evaluated. Three different feature selection algorithms (genetic search, linear forward search, particle swarm optimization) are then applied to select optimum features for NR-IQA. The selected features are then used by the support vector regression model to predict the quality score. The performance of the proposed methodology is evaluated for two multiple distorted IQA databases (LIVE multiple distorted image dataset (LIVEMD), multiply distorted image database (MDID2017)), two singly synthetically distorted IQA databases (Tampere image database (TID2013), Computational and subjective image quality database (CSIQ)), and one screen content IQA database (Screen content image quality database (SIQAD)). Experimental results show that the fusion of features from different domains gives better performance in comparison to existing multiple-distorted NR-IQA techniques with SROCC scores of 0.9555, 0.9587, 0.6892, 0.9452, and 0.7682 on the LIVEMD, MDID, TID2013, CSIQ, and SIQAD databases respectively. Moreover, the performance is further improved when the genetic search feature selection algorithm is applied to fused features to remove the redundant and irrelevant features. The SROCC scores are improved to 0.9691, 0.9723, and 0.6897 for LIVEMD, MDID, and TID2013 databases respectively.

In this paper, we present a system for automatic evaluation of the quality of a question paper. Question paper plays a major role in educational assessment. The quality of a question paper is crucial to fulfilling the purpose of the assessment. In many education sectors, question papers are prepared manually. A prior analysis of a question paper might help in finding the errors in the question paper, and better achieving the goals of the assessment. In this experiment, we focus on higher education in the technical domain. First, we conducted a student survey to identify the key factors that affect the quality of a question paper. The top factors we identified are question relevance, question difficulty, and time requirement. We explored the strategies to handle these factors and implemented them. We employ various concepts and techniques for the implementation. The system finally assigns a numerical quality score against these factors. The system is evaluated using a set of question papers collected from various sources. The experimental results show that the proposed system is quite promising.

Objectives To evaluate the effectiveness, quality and reliability of YouTube videos that address retinal detachment surgery as a source of information and education for patients. Methods Performing a YouTube search using the keyword ‘retinal detachment surgery for patients’, the first 100 videos in the search results were included in the study. The number of views, age, number of likes, number of dislikes, number of comments, length, upload source, country of origin, type (patient information and education, patient experience), and surgical technique described (pars plana vitrectomy, scleral buckling, pneumatic retinopexy) were recorded for all videos. The quality and accuracy of the information were evaluated by two independent ophthalmologists using the DISCERN, global quality and usefulness scoring systems. Results Of the top 100 videos, 77 met the inclusion criteria. When the videos were evaluated according to the source, 21 (27.3%) had been uploaded by physicians, 30 (39%) by private health institutions, 10 (13%) by health channels, eight (10.4%) by patients, seven (9.1%) by academia (university hospitals), and one (1.3%) by a pharmaceutical company. The mean DISCERN score was 53.36, the mean Global Quality score was 3.49, and the mean usefulness score was 3.86. There was a significant and strong correlation between the usefulness score and the global Quality and DISCERN scores. A significant and strong correlation was also found between the global quality score and the DISCERN score. Conclusion YouTube appears to be a platform with sufficiently informative videos in the area of retinal detachment surgery for patients. Healthcare professionals and professional and academic institutions should use this platform effectively to spread high quality information to patients and their families.

Background and study aims In borderline resectable/locally advanced pancreatic ductal adenocarcinoma (PDAC), stereotactic body radiation therapy (SBRT) is an emerging neoadjuvant treatment option. Endoscopic ultrasound (EUS)-guided insertion of fiducial markers being a prerequisite, our aim was to assess its feasibility and safety and also to evaluate its success, from both the endoscopist’s and radiotherapist’s perspectives. Patients and methods We prospectively collected data concerning PDAC patients submitted to EUS-guided fiducial placement, from February 2018 to November 2019. Technical success was defined as at least one marker presumed inside the tumor. Quality success was assessed at pre-SBRT computed tomography, accordingly to the number of markers inside or, info:eu-repo/semantics/published

Purpose: This survey aimed to investigate quality of communicating design features for the construction of cobalt chromium removable partial dentures (RPDs) among dentists in Riyadh, Saudi Arabia. Materials and Methods: A survey of nine commercial dental laboratories located in Riyadh was carried out. In each visit, master casts for cobalt chromium RPDs and dentists’ prescriptions were examined. A quality score for the provided instructions was developed and ranged from 0 to 4. A zero score means that no instructions were sent from the dentist for the design of the RPD. A score of 4 means that instructions were provided for the design of four main elements of the RPD, i.e., shape of major connector, type of direct retainers, position of direct retainers, position of dental rests. Results: 162 dentists’ prescriptions for RPDs and related casts were assessed. The majority of RPD cases were designed by the dental technician alone (64.2%). Shape of the major connector was the most frequent element in dentists’ prescriptions (35.8%). The mean quality score of dentists’ instructions was 0.96 (sd=1.54). 18% of the provided instructions achieved quality score equal to 4. Prescriptions for Kennedy Class III cases achieved significantly higher mean quality score compared to Kennedy Class II cases (p

Background: Inadequate pain management and sleep disturbances of patients undergoing gynecological surgery are associated with delayed recovery time. This study aimed to assess the effect of Jacobson’s Progressive Relaxation Technique (JPRT) on postoperative pain, activity tolerance, and sleeping quality in patients undergoing gynecological surgery. Materials and Methods: A randomized controlled clinical trial conducted at Obstetrics and Gynecology Department/Damanhour educational institute, Elbehira, Egypt. The study sample involved 116 patients undergoing gynecological surgery who were equally distributed between intervention and control groups. Data collected from April to September 2019. Four tools were used for data collection: Demographic data interview schedule, pain analog scale, activity tolerance questionnaire, and the Groningen sleeping quality scale. For the intervention group, the women were asked to perform JPRT for 30 min on the second and third postoperative day, three times a day. SPSS 23.0 is used to analyze data using Chi‑square, Fisher’s exact, independent t‑test, and Analysis of Covariance (ANCOVA). A significance level considered at p < 0.05. Results: The study results showed that JPRT significantly improves pain, sleep quality, and activity tolerance mean scores among the intervention group compared to the control group (F1 = 119.13, p < 0.001), (F1 = 361.49, p < 0.001), and (F1 = 157.49, p < 0.001), respectively. ANCOVA results showed that 33% of the decreased pain score, 12% of decreased sleeping quality score, and 26% of improved activity tolerance score are due to JPRT. Conclusion: JPRT should be offered as a part of standard postoperative nursing care for patients undergoing gynecological surgery to control pain and improve sleeping quality and activity tolerance.

The latent fingerprint examiners often mark minutiae and perform a comparison of latent fingerprints with exemplar fingerprints of known identity. The interpretation of details in the fingerprints is often based on the proficiency of examiners. Different examiners discern fingerprint regions and details differently due to an unconscious choice of certain features driven by their experiences. In this study, we aim to draw inferences from the perceptual behavior by collecting eye gaze of examiners while they mark minutiae and perform comparison. The study shows the patterns observed across different forensic examiners and infers specific heuristics used by examiners to discern features. These practices could be inculcated back into an AFIS system to improve automated comparison and help train novice examiners. To draw inferences, novice and expert examiners perform latent to exemplar fingerprint comparison by following the ACE-V mechanism. During the comparison, examiners provide a value determination, quality score, and minutiae markup with respective confidences. 29 distinct examiners perform a total of 158 trials, where, the eye gaze is recorded simultaneously. Using the eye gaze fixation, we empirically find Regions of Interest (ROI) of examiners on the prints and utilize it towards developing an understanding of the search strategy.

YouTube is a common source of medical information for patients. This is the first study to assess the reliability and educational value of YouTube videos on neurotoxin procedures. YouTube.com was searched on June 15, 2020 using the keyword “Botox” or “neurotoxin.” A total of 100 videos were reviewed. Sixty-one videos met the inclusion criteria and were included in the final analysis. Video characteristics were noted, and a score was assigned to each video using the Journal of the American Medical Association (JAMA) benchmark criteria and the Global Quality Score (GQS) to measure source reliability and educational value, respectively. A total of 61 videos that met the inclusion criteria had an average length of 589 seconds (9 minutes and 49 seconds), 210,673 views, 5,295 likes, 318 dislikes, and 478 comments. A total of 30 videos (49%) were posted with an intention to educate patients while 31 videos (51%) were posted with the intention to detail a personal experience with neurotoxin. Patient education videos were significantly more reliable (P JAMA< 0.001) and had more educational value (P GQS Key Points

We aimed to investigate whether adherence to dietary antioxidant quality score (DAQS) is associated with metabolic syndrome (MetS) among the Tehranian population. This cross‐sectional study was conducted on 270 apparently healthy adults aged between 18 and 45 years old who lived in Tehran, Iran, between February 2017 and December 2018. Participants were categorized based on tertile cut‐off points of DAQs. To examine the association between DAQS and MetS and its components, we used multivariable logistic regression analysis in different models. Adherence to DAQS was associated with a significant increase for intake of vitamin B6 (P‐value = 0.02), riboflavin (P‐value, We aimed to investigate whether adherence to dietary antioxidant quality score (DAQs) is associated with metabolic syndrome (MetS) among the Tehranian population. In conclusion, although we observed an improvement in SBP with a greater adherence to dietary antioxidant quality score, there was no association between DAQs and metabolic syndrome and its other components.

BACKGROUND: Determination of isocitrate dehydrogenase (IDH) status and, if IDH-mutant, assessing 1p19q codeletion are an important component of diagnosis of World Health Organization grades II/III or lower-grade gliomas. This has led to research into noninvasively correlating imaging features (“radiomics”) with genetic status. PURPOSE: Our aim was to perform a diagnostic test accuracy systematic review for classifying IDH and 1p19q status using MR imaging radiomics, to provide future directions for integration into clinical radiology. DATA SOURCES: Ovid (MEDLINE), Scopus, and the Web of Science were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Diagnostic Test Accuracy guidelines. STUDY SELECTION: Fourteen journal articles were selected that included 1655 lower-grade gliomas classified by their IDH and/or 1p19q status from MR imaging radiomic features. DATA ANALYSIS: For each article, the classification of IDH and/or 1p19q status using MR imaging radiomics was evaluated using the area under curve or descriptive statistics. Quality assessment was performed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the radiomics quality score. DATA SYNTHESIS: The best classifier of IDH status was with conventional radiomics in combination with convolutional neural network–derived features (area under the curve = 0.95, 94.4% sensitivity, 86.7% specificity). Optimal classification of 1p19q status occurred with texture-based radiomics (area under the curve = 0.96, 90% sensitivity, 89% specificity). LIMITATIONS: A meta-analysis showed high heterogeneity due to the uniqueness of radiomic pipelines. CONCLUSIONS: Radiogenomics is a potential alternative to standard invasive biopsy techniques for determination of IDH and 1p19q status in lower-grade gliomas but requires translational research for clinical uptake.

© 2021, The Author(s), under exclusive licence to Springer Nature Limited.Although YouTube video is one of the most widely used and easily accessible information sharing sources, its widespread use can carry the risk of spreading misleading and unreliable information. We aimed to evaluate the accuracy, reliability, quality, and content of the most viewed YouTube videos related to Peyronie’s disease treatment. The keywords of “penile curvature”, “penile deformity”, “bent penis” “curved penis”, and “Peyronie’s disease” were searched on YouTube. Among 700 YouTube videos, 267 videos were included in the study. They were categorized by two independent urologists with board certification as accurate information (n = 138, 51.7%) or inaccurate information (n = 129, 48.3%). Accurate videos contained information about the treatment of Peyronie’s disease with proven scientific accuracy according to the current guidelines, whereas inaccurate videos contained scientifically unproven or incorrect information and recommendations not in the guidelines. A 5-point modified DISCERN scale and Global Quality Score were used for reliability and quality assessment. Although the accurate information group had a significantly higher DISCERN Score (3, IQR = 3–4 vs. 1, IQR = 1–2, p

Objective\ud To evaluate the methodology of studies reporting reference ranges for fetal brain structures on magnetic resonance imaging (MRI).\ud \ud Methods\ud MEDLINE, EMBASE, CINAHL and the Web of Science databases were searched electronically up to 31 December 2020 to identify studies investigating biometry and growth of the fetal brain and reporting reference ranges for brain structures using MRI. The primary aim was to evaluate the methodology of these studies. A list of 26 quality criteria divided into three domains, including ‘study design’, ‘statistical and reporting methods’ and ‘specific aspects relevant to MRI’, was developed and applied to evaluate the methodological appropriateness of each of the included studies. The overall quality score of a study, ranging between 0 and 26, was defined as the sum of scores awarded for each quality criterion and expressed as a percentage (the lower the percentage, the higher the risk of bias).\ud \ud Results\ud Fifteen studies were included in this systematic review. The overall mean quality score of the studies evaluated was 48.7%. When focusing on each domain, the mean quality score was 42.0% for ‘study design’, 59.4% for ‘statistical and reporting methods’ and 33.3% for ‘specific aspects relevant to MRI’. For the ‘study design’ domain, sample size calculation and consecutive enrolment of women were the items found to be at the highest risk of bias. For the ‘statistical and reporting methods’ domain, the presence of regression equations for mean and SD for each measurement, the number of measurements taken for each variable and the presence of postnatal assessment information were the items found to be at the highest risk of bias. For the ‘specific aspects relevant to MRI’ domain, whole fetal brain assessment was not performed in any of the included studies and was therefore considered to be the item at the highest risk of bias.\ud \ud Conclusions\ud Most of the previously published studies reporting fetal brain reference ranges on MRI are highly heterogeneous and have low-to-moderate quality in terms of methodology, which is similar to the findings reported for ultrasound studies.

Introduction The US FDA is interested in a tool that would enable pharmacovigilance safety evaluators to automate the identification of adverse drug events (ADEs) mentioned in FDA prescribing information. The MITRE Corporation (MITRE) and the FDA organized a shared task—Adverse Drug Event Evaluation (ADE Eval)—to determine whether the performance of algorithms currently used for natural language processing (NLP) might be good enough for real-world use. Objective ADE Eval was conducted to evaluate a range of NLP techniques for identifying ADEs mentioned in publicly available FDA-approved drug labels (package inserts). It was designed specifically to reflect pharmacovigilance practices within the FDA and model possible pharmacovigilance use cases. Methods Pharmacovigilance-specific annotation guidelines and annotated corpora were created. Two metrics modeled the experiences of FDA safety evaluators: one measured the ability of an algorithm to identify correct Medical Dictionary for Regulatory Activities (MedDRA®) terms for the text from the annotated corpora, and the other assessed the quality of evidence extracted from the corpora to support the selected MedDRA® term by measuring the portion of annotated text an algorithm correctly identified. A third metric assessed the cost of correcting system output for subsequent training (averaged, weighted F1-measure for mention finding). Results In total, 13 teams submitted 23 runs: the top MedDRA® coding F1-measure was 0.79, the top quality score was 0.96, and the top mention-finding F1-measure was 0.89. Conclusion While NLP techniques do not perform at levels that would allow them to be used without intervention, it is now worthwhile exploring making NLP outputs available in human pharmacovigilance workflows. Electronic supplementary material The online version of this article (10.1007/s40264-020-00996-3) contains supplementary material, which is available to authorized users.

To assess the methodological quality and risk of bias in radiomics studies investigating diagnosis, therapy response, and survival of patients with osteosarcoma. In this systematic review, literatures on radiomics in osteosarcoma were included and assessed for methodological quality through the radiomics quality score (RQS). The risk of bias and concern of application was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. A meta-analysis of studies focusing on predicting osteosarcoma response to neoadjuvant chemotherapy was performed. Twelve radiomics studies exploring osteosarcoma were identified, and five were included in meta-analysis. The RQS reached an average of 20.4% (6.92 of 36) with good inter-rater agreement (ICC 0.95, 95% CI 0.85-0.99). Four studies validated results with an internal dataset, none of which used external dataset; one study was prospectively designed, and another one shared part of the dataset. The risk of bias and concern of application were mainly related to index test aspect. The meta-analysis showed a diagnostic odds ratio of 43.68 (95%CI 13.5-141.31) for predicting response to neoadjuvant chemotherapy with high heterogeneity and low methodological quality. The overall scientific quality of included studies is insufficient; however, radiomics remains a promising technology for predicting treatment response, which might guide therapeutic decision-making and related to prognosis. Improvements in study design, validation, and open science needs to be made to demonstrate the generalizability of findings and to achieve clinical applications. Widespread application of RQS, pre-trained RQS scoring procedure, and modification of RQS in response to clinical needs are necessary. • Limited radiomics studies were established in osteosarcoma with mean RQS of 20.4%, commonly due to unvalidated results, retrospective study design, and absence of open science. • Meta-analysis of radiomics studies predicting osteosarcoma response to neoadjuvant chemotherapy showed high diagnostic odds ratio 43.68, while high heterogeneity and low methodological quality were the main concerns. • A previously trained data extraction instrument allowed reaching moderate inter-rater agreement in RQS applications, while RQS still needs improvement to become a wide adaptive tool in reviews of radiomics studies, in routine self-check before manuscript submitting and in study design.

Background The internet is a widely used source for obtaining medical information both by patients and physicians. YouTube is an essential source of information that may be a useful tool to inform the public and may improve the learning experience if used adequately. In this study, we aimed to estimate the quality and accuracy of videos about cardiopulmonary resuscitation videos aired on YouTube, which is the most popular video platform of the online world. Methods We included the first 100 videos, in English, returned by the YouTube search engine in response to “cardiopulmonary resuscitation” keyword query to the study. The popularity of the videos was evaluated with an index called the video power index. The educational quality, accuracy, and transparency of the visual content were measured using the DISCERN questionnaire (DISCERN), Journal of American Medical Association (JAMA-BC) benchmark criteria, and Global Quality Score (GQS). The technical quality was measured by the Cardiopulmonary Resuscitation Scoring System (CPR-SS), which was utilized by three bariatric surgeons. Results The source in 7% of the videos was medical doctors. The content in 89% of the videos was cardiopulmonary resuscitation technique. According to sources, videos uploaded by physicians had significantly higher quality, transparency, educational and technical value. Unlike, videos uploaded by physicians had a lower video power index than videos uploaded by non-medical professionals. Cardiopulmonary resuscitation technique videos had significantly higher quality, transparency, educational and technical value. Cardiopulmonary resuscitation technique videos also had higher popularity scores than “information or lecture” videos. Also, negative correlations were found between the (popularity index and transparency, education and technical quality scores. Conclusions Online information on cardiopulmonary resuscitation is of low quality, and its contents are of unknown source and accuracy. However, the educational potential of the online video platform, YouTube, cannot be neglected.

Background The use of malnutrition outcome measures (OM) by registered dietitians (RD) with inpatients in hospitals has increased promoting the achievement of nutritional care goals and supporting decision-making for the allocation of nutritional care resources in hospitals. There are 3 commonly used OMs: Subjective Global Assessment (SGA), Patient Generated-Subjective Global Assessment (PG-SGA) and Mini Nutritional Assessment (MNA). The purpose of this current study was to systematically review the evidence of the clinical measurement properties of malnutrition assessment tools for use with patients admitted in hospitals. Methods MEDLINE, Cinahl, EMBASE, and PubMed were searched for articles published between 2000 and 2019. Research articles were selected if they established reliability, validity, and responsiveness to change properties of the SGA, PG-SGA and MNA tools, were written in English, and used any of these OMs as an outcome measure. Abstracts were not considered. The risk of bias within studies was assessed using the Quality Appraisal for Clinical Measurement Study (QA-CMS). Results Five hundred five studies were identified, of which 34 articles were included in the final review: SGA (n = 8), PG-SGA (n = 13), and MNA (n = 13). Of the 34 studies, 8 had a quality score greater than 75%; 23 had a quality score of 40–75% and 3 studies had a quality score of less than 40%. PG-SGA was found to have excellentdiagnostic accuracy (ROC: 0.92–0.975; Sensitivity: 88.6–98%; Specificity: 82–100%), sufficient internal consistency (Cronbach’s alpha: 0.722–0.73), and strong test-retest reliability (r = 0.866). There was insufficient evidence to suggest adequate diagnostic accuracy and good inter-rater reliability for SGA. Only one study examined the minimum detectable change of MNA (MDC = 2.1). Conclusions The evidence of validity for the existing malnutrition assessment tools supports the use of these tools, but more studies with sound methodological quality are needed to assess the responsiveness of these OMs to detect the change in nutritional status.

The aim of this study was to evaluate the content, reliability and quality of YouTube videos related to pelvic floor muscle exercise training. This study was carried out on the descriptive model in order to evaluate the content, reliability and quality of the videos on YouTube related to pelvic floor muscle exercise training. “Pelvic floor muscle exercise” was searched on YouTube in English in March 2020, and a total of 107 videos were watched. Quality Criteria for Consumer Health Information (DISCERN) survey was used to analyze the videos in terms of their reliabilities, and Global Quality Score (GQS) was used to evaluate their qualities. When the contents of 59 videos included in the study were examined, it was determined that 52 of them contained useful information and 7 of them contained misleading information. Comprehensiveness mean scores, DISCERN mean scores and GQS means of the useful videos were found to be statistically higher than that of the moderate and misleading videos (p

Evaluate quality and readability of online information for common rheumatologic diseases. Compare rheumatology patients' internet use and preferences to an objective evaluation of internet quality and readability. Five common rheumatologic diseases were searched on the web browser Google using English language. The first twenty websites from each of the five searches were evaluated for internet quality (e.g. content that is current, balanced, has specific aims, and is appropriately cited) using the DISCERN criteria and readability using the Flesch-Kincaid Grade Level (FKGL). The results were contrasted with a survey sent to patients with rheumatic disease. The survey measured patient likeliness to use and trust identified websites. Internet quality was similar (good) for all five diseases searched while readability was poor. There was an inverse relationship between internet quality and readability. Internet quality significantly differed across website sponsor, and readability significantly differed across disease and website sponsor. Common medical website sponsors with the highest combined quality and readability scores were Mayo Clinic and Web MD. Eight hundred and fifty-eight patients were sent a survey, of which 147 (17%) completed. Patients indicated they were most likely to use and trust a Mayo Clinic-sponsored website when compared to other common sponsored websites from our evaluation, followed by the American College of Rheumatology. Although we found good-quality information, all websites evaluated had readability levels above the recommended sixth-grade reading level. The website sponsor with the highest combined readability and quality score was also the most used and trusted by patients. Patients would like more information about credible and trusted websites from their medical providers.