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Traditional health systems mostly rely on rules created by experts to offer adaptive interventions to patients. However, with recent advances in artificial intelligence (AI) and machine learning (ML) techniques, health-related systems are becoming more sophisticated with higher accuracy in providing more personalized interventions or treatments to individual patients. In this paper, we present an extensive literature review to explore the current trends in ML-based adaptive systems for health and well-being. We conduct a systematic search for articles published between January 2011 and April 2022 and selected 87 articles that met our inclusion criteria for review. The selected articles target 18 health and wellness domains including disease management, assistive healthcare, medical diagnosis, mental health, physical activity, dietary management, health monitoring, substance use, smoking cessation, homeopathy remedy finding, patient privacy, mobile health (mHealth) apps finder, clinician knowledge representation for neonatal emergency care, dental and oral health, medication management, disease surveillance, medical specialty recommendation, and health awareness. Our review focuses on five key areas across the target domains: data collection strategies, model development process, ML techniques utilized, model evaluation techniques, as well as adaptive or personalization strategies for health and wellness interventions. We also identified various technical and methodological challenges including data volume constraints, data quality issues, data diversity or variability issues, infrastructure-related issues, and suitability of interventions which offer directions for future work in this area. Finally, we offer recommendations for tackling these challenges, leveraging on technological advances such as multimodality, Cloud technology, online learning, edge computing, automatic re-calibration, Bluetooth auto-reconnection, feedback pipeline, federated learning, explainable AI, and co-creation of health and wellness interventions. [ABSTRACT FROM AUTHOR]

Identifying roads' hazardous locations and solving their problems are key measures in traffic safety management. However, since the traditional hotspot identification (HSID) rests on the yearly-aggregated crashes, two problems appear: locations that become unsafe at specific short periods may remain unidentified as they may not show noticeable crash counts, and results of the problem diagnosis analysis on hotspots' crashes potentially contain a great amount of uncertainty. Even though researchers have recently added the dimension of time and analyzed accidents spatio-temporally to obtain more insights, the mentioned problems have not been addressed fully. Hence, this paper first suggests a new linear DBSCAN-based HSID method and demonstrates its acceptable performance by comparison with KDE+, the well-known clustering technique; Second, employing the proposed technique, the paper presents an algorithm for the spatial analysis of accidents through diverse time dimensions, which categorizes the risky locations based on their periodic reappearance. The tempo-categorization purpose is to enhance diagnosing causative risks by understanding their arising periods. The algorithm is tested using Allegheny highways crash data from 2014 to 2019. Results illustrate the contribution of the suggested method to problem diagnosis and detecting hidden unsafe points. [ABSTRACT FROM AUTHOR]

This meta-synthesis aimed to synthesise qualitative evidence on experiences of people with Multiple Sclerosis (MS) in receiving a diagnosis, to derive a conceptual understanding of adjustment to MS diagnosis. Five electronic databases were systematically searched to identify qualitative studies that explored views and experiences around MS diagnosis. Papers were quality-appraised using a standardised checklist. Data synthesis was guided by principles of meta-ethnography, a well-established interpretive method for synthesising qualitative evidence. Thirty-seven papers were selected (with 874 people with MS). Synthesis demonstrated that around the point of MS diagnosis people experienced considerable emotional upheaval (e.g., shock, denial, anger, fear) and difficulties (e.g., lengthy diagnosis process) that limited their ability to make sense of their diagnosis, leading to adjustment difficulties. However, support resources (e.g., support from clinicians) and adaptive coping strategies (e.g., acceptance) facilitated the adjustment process. Additionally, several unmet emotional and informational support needs (e.g., need for personalised information and tailored emotional support) were identified that, if addressed, could improve adjustment to diagnosis. Our synthesis highlights the need for providing person-centred support and advice at the time of diagnosis and presents a conceptual map of adjustment for designing interventions to improve adjustment following MS diagnosis. The period surrounding Multiple Sclerosis diagnosis can be stressful and psychologically demanding. Challenges and disruptions at diagnosis can threaten sense of self, resulting in negative emotions. Adaptive coping skills and support resources could contribute to better adjustment following diagnosis. Support interventions should be tailored to the needs of newly diagnosed people. [ABSTRACT FROM AUTHOR]

Information retrieval/memory recall by patients/carers within the medical appointment is reported to be of paramount importance to the diagnostic/decision-making process within the medical appointment and hence to the outcome of the medical encounter itself. The rationale behind this paper (second in a series of papers) is to delve into the current literature to ascertain the pervasiveness of long-term information retrieval/memory recall concepts within this intricate environment, including the disease states in which patient information retrieval/memory recall research has been conducted, affording an analysis of research activities in order to identify the gaps in knowledge that currently exist. A rigorous systematic process detected 49 papers that clearly consider information retrieval/memory recall events within the medical appointment. Content analysis was conducted using a Concept-Centric Matrix in conjunction with open-coding techniques, giving rise to the detection of 227 concepts, which were subsequently assembled into 63 categories. Our analysis reveals the prevalence of long-term information retrieval/memory recall concepts, and the disease states that have conducted patient information retrieval/memory recall research (within the medical appointment) reported in writings over the past 43 years. Additionally, we have advanced our conceptual model of memory recall/information retrieval within the elicitation phase of the medical appointment, which we first presented in an earlier paper. The current paper is of significance as it facilitates an augmented understanding of information retrieval/memory recall (and the importance of same to the diagnostic/decision-making process and to patient outcomes, within the medical appointment. Furthermore, the exploration serves to highlight a number of IS research opportunities. [ABSTRACT FROM AUTHOR]

This paper proposes a computer-aided methodology for detecting and segmenting the tumor regions in ultrasound thyroid images using machine and deep learning algorithms. This proposed tumor detection methodology uses Kirsch's edge detector for enhancing the edge region pixels in thyroid image and then Dual Tree Contourlet Transform (DTCT) was applied on the enhanced image for obtaining the coefficients. Then, features are computed from this transformed thyroid image and these features are trained and classified using the Co-Active Adaptive Neuro Expert System (CANFES) classifier. Then, the morphological segmentation method is applied on the abnormal thyroid image to segment the tumor regions. Finally, the Convolutional Neural Network (CNN) algorithm is applied on the segmented tumor regions for diagnosing them into mild, moderate and severe. [ABSTRACT FROM AUTHOR]

Detecting tumour with Magnetic Resonance imaging (MRI) has been promising in recent years. The current tumour detection strategies are used for visualising, digitising and modelling the images for medical diagnosis. Automatic tumour region segmentation from 3D MRIs is essential for monitoring, diagnosing, and planning the treatment remedies for the disease. However, manual outlining needs an anatomical understanding which requires more time and can be imprecise due to human error. Brain tumour is serious diseases whose exposure must be quick and precise. It is attained by the accomplishment of the automatic detection of the tumour using MRI. Several automatic strategies are employed in literary works, which utilise image segmentation. Here, 50 research papers are surveyed with brain tumour detection strategies like ANN, clustering, deep learning, edge-based techniques, optimisation and transformation strategies. Furthermore, complete exploration is done in terms of publication year, employed strategy, datasets utilised, execution tool, performance measures and its values. At last, the problems of classical strategies and its issues with classical brain tumour detection methods are illustrated to generate the contribution. [ABSTRACT FROM AUTHOR]

Functional Magnetic Resonance Imaging (FMRI) is a noninvasive test to analyze several medical ailments by using magnetic resonance imaging (MRI) to detect the abnormalities in the active part of the brain and evaluate the minute changes in the blood flow, which cannot otherwise be accomplished with other imaging techniques. With its vast applications in healthcare, it has become one of the most explored studies by the researcher's community, therefore, the current paper aims to address a comprehensive systematic literature review (SLR) of the application of FMRI in healthcare. The SLR scrutinized and assessed the currently available literature using inclusion and exclusion criteria. The chief motive of conducting SLR on the current research was to eradicate the biases and make it more systematic as compared to the informal literature review. The outcomes of the review state that due to accessibility of the public datasets and the data augmentation practices, the application of FMRI in Healthcare has remarkably raised from the last five years and its application is practically available for every disease diagnosis. The performance of the diagnosis of the disease is more effectual and proficient as equal to the human experts performing it manually. [ABSTRACT FROM AUTHOR]

Undiagnosed Autism Spectrum Disorder (ASD) may represent a diagnostic challenge in people who refer to specialized services for first-episode psychosis (FEP). Similarly, individuals with ASD can present newly-onset psychotic symptoms. The present review aimed to summarize the literature available on ASD and FEP to guide differential diagnosis between the two conditions and discuss the impact of ASD-FEP comorbidity on recovery. The PRISMA-ScR guidelines were followed. After conducting a comprehensive literature search, we screened 204 papers including participants with: (1) a comorbid diagnosis of FEP and ASD; (2) FEP and autistic traits; (3) separate groups of FEP and ASD. A total of 18 studies were discussed and confirmed the high prevalence of ASD or autistic traits in people referring to FEP services (up to 9% and 35% of FEP, respectively), which could negatively impact pathways to care, clinical presentation, and outcomes. Due to some similarities in ASD and FEP presentation (e.g., difficulties in social functioning), a differential diagnosis could be challenging. The features more suggestive of ASD rather than a primary FEP include illogical and concrete thinking, and a longstanding social interaction difficulty. Aberrant salience and suspiciousness can manifest in ASD, but are usually more transient, and stress-related than in FEP. Also, perceptual abnormalities are due to altered sensory processing rather than pathological hallucinations. The co-occurrence of ASD symptoms is associated with a reduced probability of clinical and functional recovery in FEP, a higher risk of suicidal behaviors, and higher unemployment rates. The kaleidoscopic manifestations of FEP require an adequate differential diagnosis that should include ASD. FEP services ought to be equipped for an adequate assessment and diagnostic formulation, which can result particularly challenging should symptoms of autism be present in adult patients. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a prevalent tumour with high morbidity rates worldwide, and its incidence among younger populations is rising. Early diagnosis of CRC can help control the associated mortality. Fungi are common microorganisms in nature. Recent studies have shown that fungi may have a similar association with tumours as bacteria do. As an increasing number of tumour-associated fungi are discovered, this provides new ideas for the diagnosis and prognosis of tumours. The relationship between fungi and colorectal tumours has also been recently identified by scientists. Therefore, this paper describes the limitations and prospects of the application of fungi in diagnosing CRC and predicting CRC prognosis. [ABSTRACT FROM AUTHOR]

This paper explores parents' experiences of breaking news and communicating to the child with cancer and their siblings, and identifies the supports parents request to help them in this role. This paper represents one component of a wider action research study which employed mixed methods to explore supports needed by parents of children with a cancer diagnosis in the Republic of Ireland. This paper reports on the survey phase of the study, which involved the distribution of a postal survey to 550 families of children in cancer treatment and remission. This survey included four open-ended questions exploring parents' experiences of breaking news and communicating about the illness to the ill child and his/her siblings. Descriptive statistics on the profile of the parents were generated with computer software package SPSS and qualitative responses were analyzed using the survey questions as the initial framework. Parents identified four interventions that helped ease the distress of these difficult conversations: coaching, resources, team engagement, and play therapy. Parents expressed concern for siblings, describing them as "suffering" and "forgotten". Parents requested four sibling-specific interventions: the creation of resources for siblings, therapeutic support, coaching for parent-sibling conversations, standardize a family meeting with the multi-disciplinary team that includes siblings. This paper demonstrates how the practical supports requested by parents which are consistent with the principles embedded within the internationally defined psychosocial standards of care could be translated into practice when supporting parents to communicate with children in the context of pediatric cancer. [ABSTRACT FROM AUTHOR]

Diabetic Retinopathy (DR) is one of the sight-threatening diseases entered the top 10 diseases that cause death worldwide. There has been tremendous growth in diabetic patients in the last decade due to lifestyle, uncontrolled diet and genetic causes. Nevertheless, the detection of Diabetic Retinopathy in an earlier stage may save the vision of many people. Imaging technologies in the medical field play a highly vital role in understanding, modelling, detecting and diagnosis of diseases. Detection of abnormalities in the retinal image will help to detect, classify and grade the disease. However, it is necessary to segment the retinal image and extract the optic disc, optic cup, retinal blood vessels and macula. The final image interprets the diagnosis of retinopathy diseases, obliging the professional medical practitioner and representatives. This paper describes a comprehensive survey of data acquisition techniques, diabetic retinopathy and the performance of purposed models in this field. The survey involves several papers comprising the research direction of a screening system and lesion segmentation of DR, disease severity grading and abnormality detection. Furthermore, research challenges are discussed and directions are suggested. [ABSTRACT FROM AUTHOR]

This research explores the experiences of Beth, a university student in the UK, as she comes to be labelled as 'dyslexic', and as she has her diagnosis taken away. Through use of Interpretative Phenomenological Analysis (IPA) and discourse analysis, the research seeks to understand how Beth made sense of these experiences, and to explore the discursive 'life' of dyslexia within this sense-making. The discussion in this paper proceeds chronologically through Beth's story, from 'struggle', to 'legitimation' to 'derogation', and concludes with a call to recognise the role of diagnosis in the field of special educational needs (SEN) from a social constructionist and relational perspective. [ABSTRACT FROM AUTHOR]

Amyloid light chain (AL) amyloidosis is the most common systemic amyloidosis. The objective of this scoping review was to map the available literature on the diagnosis of AL amyloidosis in China. The published academic papers related to the diagnosis of AL amyloidosis were screened from 1 January 2000 to 15 September 2021. Chinese patients who have suspected AL amyloidosis were included. The included studies were categorized into accuracy studies and descriptive studies based on if the studies supplied the diagnostic accuracy data or not. The information on the diagnostic methods reported by included studies was synthesized. Forty-three articles were included for the final scoping review, with 31 belonging to descriptive studies and 12 having information on diagnostic accuracy. Although cardiac involvement was second top in Chinese patients with AL amyloidosis, a cardiac biopsy was rare. Next, we found light chain classification and monoclonal (M-) protein identification were essential methods for the diagnosis of AL amyloidosis in China. In addition, some combined tests (e.g. immunohistochemistry and serum free light chain, immunohistochemistry and immunofixation electrophoresis, and serum free light chain and immunofixation electrophoresis) can increase the sensitivity of the diagnosis. Finally, several adjuvant methods (e.g. Imaging, N-terminal-pro hormone BNP, and brain natriuretic peptide test) were important for AL amyloidosis diagnosis. This scoping review details the characteristics and results of the recently published studies on diagnosing AL Amyloidosis in China. Biopsy is the most important method for AL Amyloidosis diagnosis in China. In addition, combined tests and some adjuvant methods played essential roles in the diagnosis. Further research is required to determine an acceptable and feasible diagnostic algorithm after symptom onset. REGISTRATION: INPLASY2022100096 This scoping review details the characteristics and results of the recently published studies on diagnosing Amyloid light chain (AL) Amyloidosis in China. Biopsy is the most important method for AL Amyloidosis diagnosis in China. Combined tests and some adjuvant methods played essential roles in the diagnosis. [ABSTRACT FROM AUTHOR]

With an increasing number of children diagnosed with Autism-Spectrum-Disorder in Canada, this paper focuses on how their mothers, as Asian immigrant women, experience the process of diagnosis and learn to parent their children. By taking two Asian (Korean and Chinese) mothers' critical personal narratives as major data sources, this paper aims to explore the diagnosis process of Autism-Spectrum-Disorder through a sociocultural lens on the intersectionality of (im)migrants and their cultural competence, and argues that their identity (re)construction and learning for parenting take place at the intersectionality of race, gender, class, and disability. This paper highlights possible implications for everyone involved in this 'medical' process, in the context of Canadian or other similar multicultural societies. Asian immigrant mothers usually have to deal with children with Autism-Spectrum-Disorder (ASD) and they have bitter experience of mistreatment tied to race, gender and class. This study reveals how Asian immigrant mothers struggled in their integration to Canadian society as well as their experiences of denial into Canada's medical system. The stories of these two women shed lights on the social and cultural aspects of immigrant mothers' learning strategies, including how they utilize accessible resources and networks for their children's treatment and diagnosis. This paper suggests that policymakers need to consider the social and cultural aspects of diagnosis in immigrant families to better fit their needs and provide them appropriate medical and social support. [ABSTRACT FROM AUTHOR]

Chronic encapsulated intracerebral hematoma (CEICH) is a rare type of intracerebral hematoma (ICH) with peculiar radiological features and presenting as subtle slow-growing lesion exerting mass effect. We performed a systematic review of the literature focused on diagnosis and management of patients affected by CEICH. A literature search according to the PRISMA statement was conducted using PubMed and Scopus databases and pertinent Mesh terms. All papers that reported intraventricular CEICH, or CEICH cases treated conservatively or by CT-guided needle aspiration were not included in this study. A total of 40 papers were included in this review, with 58 patients (38 males and 20 females) and a mean age of 41.44 ± 20.05 years (range 1–80). Neurological symptoms of onset include those related to an increase in intracranial pressure (ICP) in 28/58 cases (48.2%), seizures in 17/58 cases (29.3%), motor deficits in 14/58 cases (24.1%). The most frequent localization is atypical in 45/58 cases (77.6%). Surgical approach is not specified in 21/58 cases (36.2%), craniotomy was performed in 31/58 cases (53.4%), craniectomy in 5/58 cases (8.6%) and only in one case (1.7%) an endoscopic approach was performed. CEICH are usually located in an atypical site. There is not an association with anticoagulants and antiplatelets intake. Arteriovenous malformation is the most frequent cause. Surgery is suggested, and craniotomy is the most used approach even if further investigation should be directed to analyze the efficacy of endoscopic approach of these lesions, which may show favorable outcome. [ABSTRACT FROM AUTHOR]

Functional constipation is one of the common disorders of gut–brain interaction in infancy, and decreases the quality of life of infants and parents. Relevant articles up to November 2022 were reviewed. We searched in PubMed, Google Scholar, and MEDLINE for guidelines, position papers, reviews, and randomized controlled trials on infant constipation. Randomized controlled trials in this specific age group are mostly limited to trials with infant formula. The prevalence of infant constipation in formula-fed infants is decreasing, and can be associated with adaptations in formula composition. While the supplementation of infant formula with pro-, pre- and/or synbiotics decreases the prevalence of constipation, their efficacy in constipated infants is disappointing. There is limited evidence to support the addition of magnesium to infant formula to treat constipation. The evidence for the efficacy and safety of polyethylene glycol in children < 2 years has expanded over the past years. The administration of lactulose or polyethylene glycol is the preferred medical management, in case nutritional management does result in insufficient improvement. [ABSTRACT FROM AUTHOR]

Early detection and individualized treatment of patients with liver disease is the key to survival. Radiomics can extract high-throughput quantitative features by multimode imaging, which has good application prospects for the diagnosis, staging and prognosis of benign and malignant liver diseases. Therefore, this paper summarizes the current research status in the field of liver disease, in order to help these patients achieve personalized and precision medical care. This paper uses several keywords on the PubMed database to search the references, and reviews the workflow of traditional radiomics, as well as the characteristics and influencing factors of different imaging modes. At the same time, the references on the application of imaging in different benign and malignant liver diseases were also summarized. For patients with liver disease, the traditional imaging evaluation can only provide limited information. Radiomics exploits the characteristics of high-throughput and high-dimensional extraction, enabling liver imaging capabilities far beyond the scope of traditional visual image analysis. Recent studies have demonstrated the prospect of this technology in personalized diagnosis and treatment decision in various fields of the liver. However, further clinical validation is needed in its application and practice. [ABSTRACT FROM AUTHOR]

A growing body of public policy and governance scholars recognise the importance of learning in supporting adaptive and responsive governance systems. Fostering learning within policy processes and governance systems, however, can be challenging. Collectively, we often ignore or misinterpret relevant policy information, or we may be incapable of translating new information into policy. Despite significant scholarly attention to learning, knowledge of the barriers to learning remains underdeveloped. To advance theoretical insights, this article integrates research on individual cognitive biases with literature on learning to identify barriers that can block learning or lead to non-learning in policy and governance processes. It also explores how these barriers can be mitigated or exacerbated by different governance contexts. Based on these insights, this paper provides guidance for researchers on how to empirically assess learning barriers across different governance contexts. [ABSTRACT FROM AUTHOR]

Online quality control methods emphasize manufacturing processes to attain maximum conformance with respect to the specifications of the concerned quality characteristics of a product. One key factor that affects the effectiveness of these methods is the diagnosis interval. In this paper, the existing cost model along with its cost components for online quality control methods has been revisited and modified by incorporating new variables like the rate of production, the loss due to false alarm, the loss due to non-detection of process abnormalities, and considering a workable break-up of diagnosis cost for finding the optimal diagnosis interval from the perspective of present-day manufacturing engineering. As already mentioned, the proposed cost model has not ignored the loss due to the generation of defective items as well as the adjustment cost available in the pertinent literature. The modified cost function thus proposed has been appropriately minimized to obtain the corresponding optimal diagnosis interval. The proposed methodology has been compared numerically with other methodologies to establish its effectiveness. The cornerstone of the proposed methodology lies in reinforcing its effectiveness through a real-life case example in manufacturing. Sensitivity analysis has also been carried out for the real-life case example to fortify the proposed methodology. [ABSTRACT FROM AUTHOR]

There is a lack of knowledge concerning the validity of the interstitial lung disease (ILD) diagnoses used in epidemiological studies on rheumatic diseases. This paper seeks to verify register-derived ILD diagnoses using chest computed tomography (CT) and medical records as a gold standard. The Norwegian Anti-Rheumatic Drug Register (NOR-DMARD) is a multicentre prospective observational study of patients with inflammatory arthritis who start treatment with disease-modifying anti-rheumatic drugs. NOR-DMARD is linked to the Norwegian Patient Registry (NPR) and Cause of Death Registry. We searched registers for ILD coded by ICD-10 J84 or J99 among patients with rheumatoid arthritis, psoriatic arthritis, or spondyloarthritis. We extracted chest CT reports and medical records from participating hospitals. Two expert thoracic radiologists scored examinations to confirm the ILD diagnosis. We also searched medical records to find justifications for the diagnosis following multidisciplinary evaluations. We calculated the positive predictive values (PPVs) for ILD across subsets. We identified 71 cases with an ILD diagnosis. CT examinations were available in 65/71 patients (91.5%), of whom ILD was confirmed on CT in 29/65 (44.6%). In a further 10 patients, medical records confirmed the diagnosis, giving a total of 39/71 verified cases. The PPV of a register-derived ILD diagnosis was thus 54.9%. In a subset of patients who had received an ILD code at two or more time-points and had a CT scan taken within a relevant period, the PPV was 72.2%. The validity of register-based diagnoses of ILD must be carefully considered in epidemiological studies. [ABSTRACT FROM AUTHOR]

Acute lymphoblastic leukemia (ALL) is a debilitating illness that easily occurs in adolescents. microRNAs (miRNAs) are potential biomarkers for multiple diseases. This paper was to elaborate on the expression of miR-16-2-3p in childhood ALL and its clinical values on ALL diagnosis and prognosis. First, serum miR-16-2-3p expression in ALL children and healthy volunteers was measured using RT-qPCR. Next, diagnostic potential and prognostic values of miR-16-2-3p on ALL were analyzed through receiver operating characteristic (ROC) curve, Kaplan–Meier survival curve, and multivariate Cox regression analysis, respectively. No significant difference was observed in the clinical baseline data between ALL patients and healthy children. ALL patients showed downregulated serum miR-16-2-3p (0.65 ± 0.27) (p <.01), whose area under the ROC curve was 0.837 with a cut-off value of 0.745 (67.92% sensitivity, 96.94% specificity). ALL patients with higher miR-16-2-3p expression had higher survival rates than those with lower miR-16-2-3p expression. Low miR-16-2-3p expression predicted poor prognosis of ALL patients. After adjusting LDH and lymphomyelocyte proportion (p = 0.003, HR = 0.003, 95%CI = 0.000–0.145), miR-16-2-3p was recognized as an independent prognostic factor for ALL patient survival. Briefly, low serum miR-16-2-3p expression in ALL children could aid ALL diagnosis and predict poor prognosis. [ABSTRACT FROM AUTHOR]

The EU Commission's proposal for the Regulation on Artificial Intelligence, whilst providing important specifications on the importance of transparency of high-risk systems, falls short in providing a nuanced picture of how technical safeguards in Articles 13 and 14 in the proposal should be translated to AI systems operating on the ground. This paper focusing on medical diagnostic systems offers a perspective on how transparency safeguards should be applied in practice, considering the role of post hoc explainability and Uncertainty Estimates in medical imaging. Medical diagnostic systems offer probabilistic judgements regarding disease classification tasks, having an impact on the interactive experience between the doctor and the patient. Accordingly, we need additional guidance regarding Articles 13 and 14 in the proposal, considering the role of shared decision-making, and patient autonomy in healthcare and to ensure that technical safeguards secure medical diagnostic systems that are a safe, reliable, and trustworthy. [ABSTRACT FROM AUTHOR]

To analyse the versatility and adaptability of commercially available exoskeletons for mobility assistance and their adaptation to diverse pathologies through a review of clinical trials in robotic lower limb training. A computer-aided search in bibliographic databases (PubMed and Web of Science) of clinical trials published up to September 2020 was done. To be selected for detailed review, clinical trials had to meet the following criteria: (1) a protocol was designed and approved, (2) participants were people with pathologies, and (3) the trials were not a single case study. Clinical trial data were collected, extracted, and analysed, considering: objectives, trial participants, number of sessions, pathologies involved, and conclusions. The search resulted in 312 potentially relevant studies of seven commercial exoskeletons, of which 135 passed the preliminary screening; and 69 studies were finally selected. Of the 69 clinical trials included in the review about 50% involved Spinal Cord Injury participants, while roughly 25% focussed on stroke and two trials corresponded to patients with both disorders. The rest were composed of neurological diseases and trauma disorders. The use of a single wearable robot for different medical conditions in various diseases is a challenge. Based on this comparative, the properties of the exoskeletons that improve the working ability with different pathologies and patient conditions have been evaluated. Suggestions were made for developing a new lower-limb exoskeleton based on various modules with a distributed control system to improve versatility in wearable technology for different gait pattern progression. Wearable robotic exoskeletons for gait assistance have been analysed from the perspective of adaptation to different diseases. This paper emphasizes the importance of personalized therapies and adaptive assistive technology. Suggestions were made for a new modular exoskeleton capable of addressing the issue of low versatility characterizing currently wearable assistive technology. [ABSTRACT FROM AUTHOR]

This paper deals with a method of segmenting skin and skin grafts using GrowCut. The previous lacks system usability because the evaluating physician needed approximately 100–200 mouse clicks for each image to acquire training data. Therefore, we propose a method to automate the acquisition of training data while maintaining the accuracy of domain segmentation from the previous study. Based on the proposed method, the ratio of the two areas-of-interest was calculated as the burn ratio and used to evaluate treatment quantitatively. The results show that the segmentation of skin and skin grafts is as accurate as by mouse clicks. We think that automating the acquisition of training data as preprocessing will improve the usability of the system. [ABSTRACT FROM AUTHOR]

Since the volume of the medical data is increasing due to the presence of vast amount of features, the conventional rule mining technique is not competent to handle the data and to perform precise diagnosis. For instance, this paper intends to implement the improved rule mining technique to overcome the above mentioned limitations. The model comes out with two main contribution stages (i) Using Map Reducing Framework (ii) Classification. Initially, the input medical data is given to map reduce framework. Here, Multi-linear Principal Component Analysis (MPCA) is used for reducing the given bulk data. Then, the reduced data is given to the classification process, where it classifies the disease with high accuracy. For this, this paper uses Support Vector Machine (SVM) classifier. After the completion of implementation, the proposed model compares its performance over other conventional methods like Principal Component Analysis- NN (PCA-NN), Independent Component Analysis- NN (ICA-NN), MPCA-NN, PCA-SVM and ICA-SVM, respectively in terms of performance measures like accuracy, specificity, sensitivity, precision, False Positive Rate (FPR), False Negative Rate (FNR), Net Present Value (NPV), False Discovery Rate (FDR), F1Score, and Mathews Correlation Coefficient (MCC), and the superiority of proposed model is proven over other methods. [ABSTRACT FROM AUTHOR]

Benign gynaecological conditions (BCGs) and body image-related concerns are commonly experienced by reproductive-aged female-identified individuals. Qualitative evidence from cancer populations identifies a link between diseases of the sexual organs and body image distress encompassing appearance, sensory and functional aspects. Most BCGs and the impacts on body image have been studied separately. However, commonalities exist between these conditions including chronicity, diagnostic delays, and menstrual-related social stigma. This systematic scoping review and meta-synthesis aimed to compare and contrast the experience of body image in the benign conditions of endometriosis, polycystic ovarian cysts, uterine fibroids, and vulvar intraepithelial neoplasia. Electronic databases (MEDLINE, PsycINFO, Scopus, CINAHL, Embase, and Allied and Complementary Medicine) were searched in February 2020 and relevant articles were examined to identify papers that qualitatively explored the relationship between body image and BCGs. Meta-synthesis was used to analyse the 17 papers that met the inclusion criteria. Six main themes evolved from this iterative analysis: loss of control; regained control; silence – menstrual concealment; cultural differences; feeling abnormal, and functional impairment. Body image concerns were widespread although impacts on individual's lives were dependent on the unique symptom profile of each disease which interacted with socio-cultural factors, daily functioning, and feminine identity. Body image concerns were a common, but hidden, experience rarely screened in routine clinical settings despite causing significant distress. The chronicity and severity of individuals unique symptom profile often determined the intensity and type of body image concerns individuals described. Across conditions, body image concerns were often left untreated, were concealed, and were associated with reduced quality of life. [ABSTRACT FROM AUTHOR]

Definitions of disability are changing, shifting from a narrow medical diagnosis to a biopsychosocial model of disability, where disability is conceptualised as a series of relational conditions that can potentially disadvantage individuals within environments. Implications of this new understanding of disability will have significant effects in the higher education sector, where there is increasing participation of disabled students. In this paper, we discuss one aspect of these implications through the topic of graduate employability. In doing so, we generate a new concept 'Employability for Inclusion' that can be utilised as an equity-focused lens for universities to consider how employability initiatives are inclusive to disabled and/or diverse students. To unpack this concept, we further illustrate how a biopsychosocial model of disability would impact key employability activities (e.g., work-integrated learning) and provide valuable insights into how the higher education sector can adopt emerging conceptualisations of disability and inclusion. [ABSTRACT FROM AUTHOR]

AbstractPurposeMethodResultConclusionThe identification of developmental language disorder (DLD) is challenging for clinicians who assess bilinguals. This paper introduces a protocol-based approach, the Bilingual Multidimensional Ability Scale (B-MAS), for expert raters to identify DLD in bilinguals.Three bilingual speech-language pathologists (SLPs) reviewed 166 Spanish-English bilingual children’s profiles, which included performance on direct (morphosyntax, semantics, and narrative tasks) and indirect (parent/teacher survey) measures in both languages. A multidimensional scale (0–5) was adopted to rate children’s performance. A diagnosis of DLD was made if at least two raters assigned a summary rating of ≤2.Analysis of the scores on the B-MAS resulted in the identification of 21 children as having DLD. Though different strategies were employed to make decisions, the three SLPs demonstrated high inter-rater agreement across different ratings (intraclass correlation coefficient values ranged from .83 to .90).For bilingual populations that are understudied and for which gold standards of assessment are not available, the B-MAS can be adopted as a starting point to study DLD or as a reference standard to develop new assessment tools in that population. Clinically, this protocol could be tailored and evaluated by a group of SLPs serving a large population of a particular bilingual group for diagnostic purposes. [ABSTRACT FROM AUTHOR]

The diagnosis of lung disease is a challenging process that frequently combines clinical information, such as patient symptoms, medical history and test findings, with medical imaging, like X-rays or CT scans. The classification of lung diseases is very important in healthcare since it helps with diagnosis and treatment of many different lung diseases. A precise classification of lung conditions can aid doctors in choosing the best course of action and enhancing patient outcomes. Additionally, accurate classification can aid in evaluating the effectiveness of therapies, forecasting results and tracking the development of diseases. It is extremely important to accurately classify lung conditions. A comparison of a novel model for lung disease classification from chest CT and CXR images was presented in this paper. A modified VGG-16 model was used as the classification model. To improve the performance, a fine-tuning mechanism was added to the proposed model. The effectiveness of the suggested method is analyzed and compared on two distinct datasets in terms of performance metrics. The experimental outcomes showed that the suggested model performs better on the CXR image dataset. [ABSTRACT FROM AUTHOR]

A fast and precise diagnosis is crucial for the treatment and management of lung diseases, which are a major global cause of morbidity and mortality. Medical diagnosis and treatment planning depend heavily on the classification of lung diseases. The correct diagnosis and classification of many lung disease types is crucial for effective management and treatment. Radiologists with training evaluate medical images subjectively in order to classify lung diseases using traditional approaches. This paper proposed an effective technique for classifying lung diseases from CXR images. For the accurate classification of lung disorders, three distinct fine-tuned models are proposed. The effectiveness of the suggested fine-tuned models was evaluated using a newly developed CXR image dataset. According to the experimental findings, the proposed fine-tuned models outperformed the existing lung disease categorization models the accuracy is 98%. The suggested approach can effectively be used for lung disease classification. [ABSTRACT FROM AUTHOR]

Many have suggested different ways of conceptualizing mental health conditions in mental health services. However, eliciting the unicity of the individual experience of mental health conditions in the diagnostic process remains challenging. In this position paper, we describe the diagnostic process in psychiatry and outline three challenges for which insights from the design research paradigm, in particular so-called generative sessions, may represent an opportunity for innovation. We suggest that by implementing generative sessions, conversations about individual experience can be initiated, the focus on diagnostic categories can be shifted towards personal variation, and the integration of empirical evidence of recovery can be facilitated. Therefore, we argue that exploring generative sessions in the diagnostic process can stimulate incremental and iterative advancements in diagnostic systems. To test its hypothesized impact on clinical practice, we recommend several directions for further research in co-creation with traditional mental health professionals, people with mental health conditions, and people with lived experience. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is an etiologically heterogeneous neurodevelopmental condition that eludes a single explanation or cure. Epidemiological studies reveal risk factors, relevant comorbidities, and behavioral correlates to reach a better understanding of ASD. To contribute such data from an understudied ASD population, this paper presents epidemiological data from a Turkish sample of individuals with ASD (n = 911, 748 boys (82.1%) and 163 girls (17.9%) between 1 and 18 years of age). Average age at diagnosis was 31.06 ± 11.88 months, and the male-to-female ratio was 4.6:1. Three in 4 individuals with ASD had obsessive behaviors, and 1 in 4 had allergic conditions, inappropriate sexual behaviors, self-harming behaviors, and harmful behaviors towards others. One in 3 received a dietary treatment for at least 3 months; almost half received vitamin supplements; the majority (70%) did not experience constipation; and 2 in 3 were picky eaters. This paper presents data on the age of diagnosis, gender ratios, accompanying behaviors, and dietary interventions in Turkish individuals with ASD, which are topics of current research interest about ASD. Such data from non-Western populations may supplement epidemiological knowledge gained from Western populations to help reach a more comprehensive understanding of this condition with many unknowns. [ABSTRACT FROM AUTHOR]

Visual neglect is a frequent and disabling consequence of right brain damage. Traditional paper-and pencil tests of neglect have limited sensitivity and ecological validity. The Baking Tray Task (BTT), instead, approaches real-life situations, because it requires participants to place 16 physical objects on a board. The number of objects placed on the left and right portions of the board provides a clinical index of visual neglect. Here we present E-TAN, a technology-enhanced platform for BTT (E-BTT). E-BTT automatically determines the object locations on the board, and also records the sequence and timing of their placement. We used E-BTT to test 9 patients with right hemisphere damage and compared their performance with that obtained by 115 healthy participants. To this end, we developed a new method of analysis of participants' performance, based on the use of the convex hull described by the objects on the board. This measure provides an estimate of the portion of space processed by each participant and can effectively discriminate neglect patients from patients without neglect. E-TAN allows clinicians to assess visuospatial performance by using a convenient, fast, and relatively automatized procedure, that patients can even perform at home to follow-up the effects of rehabilitation. [ABSTRACT FROM AUTHOR]

This article suggests the relevance of diffusionism in discussing the past, the present, and the future of the International Relations (IR) norm diffusion literature. The paper argues, thus, that IR norm research has reproduced the diffusionist and beyond-diffusionist mechanisms and epistemologies that the anthropological research on culture diffusion has developed, and this has been consequential for the discipline. Accordingly, the diffusionism dominant in the mainstream IR norm research has led to the normalisation of normative hierarchies and power asymmetries between geographies in the diffusion context. The critical norm research, complementarily, while extensively criticising such biased scholarly practices, failed to diagnose the problem as diffusionism and thus failed to benefit from the informed conclusions the anthropological schools offered regarding beyond-diffusionism in diffusion research. The paper takes this as a basis for highlighting the necessity to further extend the dialogue between IR and social sciences and humanities on issues including diffusion. [ABSTRACT FROM AUTHOR]

A lot of previous studies have shown a great interest in connecting photovoltaic (PV) arrays to electric power grids. A Maximum Power Point Tracker (MPPT) controlled 100 kW PV array to boost its power that feeds the grid with the help of a three-level inverter. This paper investigated the effects of open-circuit faults of three-level inverter IGBT switches on the performance of the PV array system. This paper proposes a new diagnostic method called the Double Threshold-Trigonometric Coordinates (DT-TC) that relies on the double threshold technique and the trigonometric coordinates, respectively, for early detection and the precise location of open-circuit faults. To the best knowledge of the authors, two simultaneous open-circuit faults were not considered in the previous studies. The obtained simulation results prove the great success of the proposed diagnosis method even under noticeable changes in irradiation, temperature, and the number of PV array connected in series and in parallel. In this study, the reconfigurable fault-tolerant inverter was included to ensure the perfect continuity of the PV array system and its recovery in an extremely very short time up to 7 ms. [ABSTRACT FROM AUTHOR]

The psychological wellbeing of Queer and Gender Diverse Young People (QGDYP) has received attention of late, and increasing research evidences much higher rates of psychological distress experienced by these groups, compared to their straight, cisgender counterparts. Far more limited is research exploring queer and gender diverse young people's own perspectives on their psychological wellbeing, an absence we address with the current study. We interviewed 21 queer or gender diverse 16–18-year-olds in Aotearoa New Zealand about their understandings of mental health and wellbeing. We took a critical realist thematic approach to analysis. This paper focuses on how participants made sense of their own distress. We explore and unpack three intersecting key themes around: 1) cisheterosexism, but not personally affected; 2) dismissal of QGDYP; and 3) validation and comfort in the biomedical model. We discuss the tensions of articulating these positions and (also) challenging cisheterosexism, and the implications for recognising and reducing the distress experienced by queer and gender diverse youth. We aim to inform policy and practice to support and ultimately improve psychological wellbeing for queer and gender diverse young people. [ABSTRACT FROM AUTHOR]

For successful prognosis of cardiovascular diseases (CVDs), an early and quick diagnosis is essential. Heart disease and strokes are the predominant causes and account for more than 80% of CVD deaths, whilst one-third of these deaths occurs prematurely in people under 70 years of age. For CVD diagnosis, patients need to show an elevated level of biomarkers in the blood sample associated with severe pain in the chest, and diagnostic electro-cardiogram (ECG). The majority of CVD patients making CVD diagnosis difficult for physicians show a surprisingly normal ECG pattern. Artificial intelligence techniques can radically improve and optimize CVD outcomes. AI has the potential to provide novel tools and techniques to collect and interpret data and make faster and more accurate decisions reducing hospitalization cost, thereby increasing the quality of life. AI has also improved medical knowledge by unlocking clinically relevant information from the voluminous and complex data received from various resources. This paper reviews the present biosensors and describes various AI techniques, which can effectively be used for early and accurate detection of CVD, thereby improving cardiac care. [ABSTRACT FROM AUTHOR]

Identify original articles that analyzed the diagnostic value of miR-21 in hepatocellular carcinoma without language restriction or publication date. We performed structured searches on PubMed, Web of Science, VHL, and EMBASE. The Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields was used to assess the quality of each study. Random effect models were used to study heterogeneity, evaluated based on the Higgins I2 statistic. 12 articles were evaluated and contained raw data from 1,329 individuals, of which 617 had HCC, 473 were healthy, and 239 had Chronic liver disease. The combined sensitivity and combined specificity of miR-21 for diagnosing HCC were, respectively, 0.83(95% CI:0.78-0.89) and 0.85(95% CI:0.80-0.90). The sensitivity and specificity, in that order, by type of control were 0.81 (95% CI: 0.71-0.91) and 0.88 (95% CI: 0.82-0.93) for CLDs and 0.86(95% CI: 0.81-0.91) and 0.83(95% CI:0.74-0.91) for Healthy controls. miR-21 has a moderate overall performance in diagnosing HCC and may serve as a potential non-invasive marker for this early-stage disease. Thus, it may contribute to complementing the results of alpha-fetoprotein in the diagnosis and help to detect HCC at an earlier stage, increasing the survival chances of these patients. [ABSTRACT FROM AUTHOR]

The methodology in this paper ran through testing iterations on data points that were also used as training data points in other folds, potentially overfitting the model to the training data and producing biased results. We read with great interest the article by Chu et al.[1] While the prospect of employing machine learning for diagnostic purposes is exciting, we found several issues with the way the technique described in this paper was designed and executed. [Extracted from the article]

PS-I learning approaches with an initial problem-solving phase (PS) followed by an instruction phase (I) can be optimised by providing adaptive (individualised) instruction that builds on students' problem-solving products. A computer-based implementation of both phases offers the possibility of adaptivity at the transition from the problem-solving to the instruction phase. However, it also poses two challenges for the problem-solving phase, which should allow for (1) complex problem-solving processes (process validity) and (2) accurate diagnosis of problem-solving products. Increased openness of the learning environment can increase the process validity and decrease diagnostic accuracy and vice-versa (complexity-accuracy trade-off). Using two variants of a computer-based learning environment for fraction comparison with different extent of openness (O+ and O-), we investigate whether both requirements (complex problem-solving processes and accurate diagnosis of the problem-solving products) can be met simultaneously. To check process validity (complexity of problem-solving processes), we compare the problem-solving products with those from previous research on an analogous paper-based version. Our results show that valid and comparable problem-solving processes can be achieved in both computer-based learning environments (O+ and O-). Moreover, only the learning environment O- enables an accurate computer-based interpretation of students' products and thus resolving the complexity-accuracy trade-off. [ABSTRACT FROM AUTHOR]

Purpose: High-grade gliomas (grade 3 and grade 4) are known to be highly locally invasive and distant metastasis though known, rarely manifest clinically due to poor survival. Recently, due to increasing survival in view of early diagnosis at relatively young age, more cases of extra neural symptomatic metastasis are being diagnosed and treated. Among these, symptomatic spinal metastasis is even more rare. Dissemination of GBM to the spinal compartment, albeit uncommon, has an even poorer outcome, with most patients dying within 2-3 months after diagnosis of metastatic disease. Materials and Methods: Here, we present a rare case report of a 25-year-old female with transformed/ histologically progressed tumour in cranial region along with ultra-rapid progression of the spinal disease following metastasis. Proper consent of the patient relatives was taken prior to production of material as patient had expired by the time of writing of this paper. We also present an extensive review of spinal metastasis secondary to intracranial high-grade gliomas starting from 1950. We conducted a thorough and exhaustive systematic search and review of the indexed databases available in PUBMED, COCHRANE and GOOGLE SCHOLAR with key words 'spinal metastasis of glioma', 'spinal metastasis', 'glioma progression', 'secondary glioma', multicentric glioma', 'secondary spinal metastasis' and formulated a comprehensive table of the studies that met the set standards. The studies that included (a) Number of cases, (b) Age and sex of patients, (c) operated primary or non-operated primary with spinal metastasis, (d) time period from the index cranial surgery, (e) outcome after diagnosis of spine metastasis and (f) histopath-ology of both cranial and spinal tumour either following surgery or autopsy have been elucidated herewith. We searched the databases with no particular time period. Out of 42 case reports and series, 28 studies were selected for our publication as they met the standards set, starting from 1950 to 2020. Results: In this case, the primary histopathological diagnosis post cranial tumour removal was Grade-3 anaplastic astrocytoma, whereas Spinal autopsy report done 16 months after the primary diagnosis showed Grade-4 GBM suggestive of secondary transformation (Secondary GBM), it showed same genome of IDH mutation and ATRX loss, neoplastic fibrillary and gemistocytic astrocytes with de-differentiation, foamy histiocytes as seen in primary lesion suggestive of progression and metachronicity rather than multicentricity or synchronicity. What is more peculiar and rare in our case is that the spinal disease was very malignant and it progressed in course of just two days to involve the whole spine. [ABSTRACT FROM AUTHOR]

Currently, the number of students in the UK with diagnoses of mental health or psychiatric conditions is rising, as are the number of students categorised as having a special educational need or disability (SEND). To support these students' objective evidence of deficit or difficulty is required, this usually takes the form of a legitimising diagnosis. However, in the case of mental health conditions, social, emotional and behavioural problems or even in some neurodevelopmental disorders, diagnosis is less useful as there are fundamental problems with the classification and understanding of mental health conditions. Despite this, the prevalence and importance of diagnosis remains in supporting students in education and those who are categorised as SEND. Therefore, this paper seeks to discuss the place that diagnosis has in education and the alternative models that exist in an effort to understand potential other avenues of supporting students and the benefits and limitations of these. [ABSTRACT FROM AUTHOR]

Melancholia is a severe form of depression that is typified by greater genetic and biological influence, distinct symptomatology, and preferential response to physical treatment. This paper sought to broadly overview potential biomarkers of melancholia to benefit differential diagnosis, clinical responses and treatment outcomes. Given nuances in distinguishing melancholia as its own condition from other depressive disorder, we emphasised studies directly comparing melancholic to non-melancholic depression. A comprehensive literature search was conducted. Key studies were identified and summarised qualitatively. 105 studies in total were identified. These studies covered a wide variety of biomarkers, and largely fell into three domains: endocrinological (especially cortisol levels, particularly in response to the dexamethasone suppression test), neurological, and immunological (particularly inflammatory markers). Less extensive evidence also exists for metabolic, genetic, and cardiovascular markers. Definitive conclusions were predominantly limited due to substantial heterogeneity in how included studies defined melancholia. Furthermore, this heterogeneity could be responsible for the between- and within-group variability observed in the candidate biomarkers that were examined. Therefore, clarifying these definitional parameters may help identify underlying patterns in biomarker expression to improve diagnostic and therapeutic precision for the depressive disorders. [ABSTRACT FROM AUTHOR]

This scoping review focused on parents' resolution of their reactions to receiving a diagnosis for their child, based on Marvin and Pianta's model and Reaction to Diagnosis Interview (RDI). We aimed to map the populations examined, the prevalence of parents' narrated resolution, and what is known about its outcomes and determinants. A structured search identified 47 peer-reviewed papers published between 1992–2021. All employed the RDI and most had a cross-sectional design. Studies focused on a wide range of children's health and mental health diagnoses. Days to years after receiving the diagnosis, RDI narratives of 18.43% to 72.49% of the parents (44% on average) indicated lack of resolution. Studies reported associations between unresolved narratives and children's insecure attachment, higher parenting stress, and poorer parental health. However, findings on the associations of narrated resolution with parents' representations of their child, sensitivity, and psychological symptoms were equivocal, and findings on factors that may shape narrated resolution were limited. To advance the understanding of parents' narrated resolution and its effects, we recommend researchers employ prospective and longitudinal designs, evaluate narrated resolution as a continuous phenomenon, focus on outcomes derived from attachment theory, and systematically sample families from heterogenous cultures. [ABSTRACT FROM AUTHOR]

Artificial Intelligence is revolutionizing the world. In the last decades, it is applied in almost all fields especially in medical prediction. Researchers in artificial intelligence have exploited predictive approaches in the medical sector for its vital importance in the process of decision making. Medical prediction aims to estimate the probability of developing a disease, to predict survivability and the spread of a disease in an area. Prediction is at the core of modern evidence-based medicine, and healthcare is one of the largest and most rapidly growing segments of AI. Application of technologies such as genomics, biotechnology, wearable sensors, and AI allows to: (1) increase availability of healthcare data and rapid progress of analytics techniques and make the foundation of precision medicine; (2) progress in detecting pathologies and avoid subjecting patients to intrusive examinations; (3) make an adapted diagnosis and therapeutic strategy to the patient's need, his environment and his way of life. In this research, an overview of applied methods on the management of diseases is presented. The most used methods are Artificial Intelligence methods such as machine learning and deep learning techniques which have improved diagnosis and prognosis efficiency. [ABSTRACT FROM AUTHOR]

Critique has been recently accused of not being able to respond to the challenges of our times, such as the climate emergency and the pandemic crisis. The new materialisms, which have posited themselves as a corrective to critique's alleged overinflation of culture and language by proposing a (re)turn to matter, affirm that ours is a post-critical era. Against this diagnosis, the aim of this paper is to defend both the importance of critique for our current conjuncture and the need to rethink what it involves. Drawing from the work of Foucault, Deleuze, and Butler, I develop a specific but multidimensional understanding of critique that combats the vagueness and inconsistencies surrounding many post-critical approaches to this notion. Specifically, I suggest that critique entails (1) an enquiry into the conditions that structure, organise, and determine what can and cannot be perceived, experienced, and thought; (2) a clinical diagnosis or symptomatology of our present; (3) a political exercise of freedom; and (4) a practice of care. I conclude by showing how this conception of critique helps us to understand different dimensions of the Covid pandemic that might otherwise be ignored. [ABSTRACT FROM AUTHOR]

Existing studies have confirmed the accuracy of arterial spin labeling (ASL) in differentiating between primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG). We aimed to consolidate the existing evidence with a meta-analysis. Six literature databases were searched for relevant papers. After assessing the quality of studies, bivariate regression was performed, and the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score, diagnostic odds ratio (DOR), and the area under the curve (AUC) of the summary receiver operating characteristic (SROC) curve were calculated, along with the corresponding 95% confidence intervals (CIs). Deeks' test was used to determine risk of publication bias. Ten high-quality studies, comprising 151 patients with PCNSL and 455 with HGG, were included. The pooled SEN was 0.79 (95% CI: 0.72–0.85), pooled SPE was 0.90 (95% CI: 0.84–0.94), pooled PLR was 8.07 (95% CI: 5.01–13.02), pooled NLR was 0.23 (95% CI: 0.17–0.32), pooled diagnostic score was 3.56 (95% CI: 2.94–4.18), and pooled DOR was 35.10 (95% CI: 18.83–65.45). The AUC of SROC was 0.86 (95% CI: 0.83–0.89). No publication bias was found. ASL demonstrated high diagnostic accuracy in differentiating between PCNSL and HGG. [ABSTRACT FROM AUTHOR]

Chronic pancreatitis (CP) is a fibroinflammatory disease complicated by episodes of acute inflammation (acute on chronic pancreatitis (ACP)). This entity is common, variably defined and can reflect different pathological mechanisms that requires different interventions. The aim of this study is to conduct a systematic review of how ACP is described, defined and diagnosed in the literature. A systematic search was conducted from January 1993 to June 2020. All articles that used a term to describe ACP in adults were reviewed and definitions and diagnostic criteria were sought. After reviewing 2271 abstracts, 848 articles included a term to describe ACP. The most common descriptions were 'acute on/in CP' (374), 'acute exacerbation of CP' (345) and 'flare(-up) of CP' (43). Among the 848 articles, 14 included a pragmatic definition of ACP, and only 2 papers stated diagnostic criteria. These covered both acute inflammation and acute exacerbation of chronic abdominal pain. There is no universally accepted term, definition or diagnostic criteria for ACP. A consensus definition is needed to improve quality and comparability of future articles as well as clinical management. [ABSTRACT FROM AUTHOR]

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Biomedical discourse commonly associates the emergence of psychosis in women with the reproductive body, most particularly, with the hormonal shifts that accompany the reproductive cycle during menstruation, pregnancy/birth, and menopause. This paper argues that hormonal theories of psychosis and the female body mirror patriarchal ideas regarding women's "raging hormones" and inherent emotional instability. Although psychosocial scholarship on psychosis has led to a broadening of the conversation regarding people diagnosed with psychotic disorders such as schizophrenia, psychoses of the female body (e.g., postpartum psychosis, menopausal psychosis, menstrual exacerbation) have thus far been neglected by this important critical analysis. The author suggests a closer engagement with feminist psychology as a way of illuminating more holistic approaches to psychosis in women, thus counterbalancing sexist and reductive narratives. [ABSTRACT FROM AUTHOR]