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Context.—Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. Its basic function is to digitize glass slides, but its impact on pathology workflows, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and intrainstitutional and interinstitutional collaboration exemplifies a significant innovative movement with far-reaching effects. Although the benefits of WSI to pathology practices, academic centers, and research institutions are many, the complexities of implementation remain an obstacle to widespread adoption. In the wake of the first regulatory clearance of WSI for primary diagnosis in the United States, some barriers to adoption have fallen. Nevertheless, implementation of WSI remains a difficult prospect for many institutions, especially those with stakeholders unfamiliar with the technologies necessary to implement a system or who cannot effectively communicate to executive leadership and sponsors the benefits of a technology that may lack clear and immediate reimbursement opportunity.Objectives.—To present an overview of WSI technology—present and future—and to demonstrate several immediate applications of WSI that support pathology practice, medical education, research, and collaboration.Data Sources.—Peer-reviewed literature was reviewed by pathologists, scientists, and technologists who have practical knowledge of and experience with WSI.Conclusions.—Implementation of WSI is a multifaceted and inherently multidisciplinary endeavor requiring contributions from pathologists, technologists, and executive leadership. Improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology, can help prospective users identify the best path for success.

William Osler combined many excellent characteristics of a clinical educator being a scientific scholar, a motivational speaker and writer and a proficient physician. As we celebrate his life a century on, many of his educational ideals are as pertinent today as they were in those Victorian times. Osler’s contributions to modern medicine go beyond his legacy of quotable aphorisms to a doctor, educator and leader whose proponent use of bedside teaching, careful clinical methods, and clinicopathological correlation was a great inspiration for students and junior doctors. He was also a great advocate of patient-centred care—listening to and closely observing his patients, an important message for modern medicine as the reliance on investigations strains modern healthcare systems. This review of Osler’s contribution to medical education summarises his development as an educator and provides reflection on his influences to modern clinical education.

Newborn screening (NBS)3 has been acclaimed by the Centers for Disease Control and Prevention as one of the most successful public health programs of the 21st century (1). In 2013, we celebrated the 50th anniversary of NBS, and these 50 years were marked by many successes. An estimated 200 million newborns in the US have been screened during that period for at least 1 disorder, phenylketonuria. Today's screening effort detects >10 000 newborns with certain heritable disorders from the 4 million screened annually. Most of these disorders cause severe, nonreversible harmful effects if not identified and treated before the onset of symptoms (2). NBS programs have evolved as new technologies have been introduced from covering 1 disorder to presently 33 recommended disorders in the US (3, 4). All NBS programs in the US collect blood samples on US Food and Drug Administration–cleared filter paper collection devices (5). Only 2 commercial sources are presently approved for use in device production and dried blood spot (DBS) collection. The filter papers, Whatman Grade 903 and Ahlstrom Grade 226, are made from high-purity cotton linters and manufactured to yield accurate and reproducible blood samples according to the Clinical and Laboratory Standards Institute's specifications (NBS01-A6) (5). Under controlled conditions, the filter paper blood collection device for NBS can achieve the same level of precision and reproducibility expected from clinical methods that typically use blood collected in vacuum tubes or capillary pipettes (6). Unlike these liquid collection devices, filter paper exhibits different levels of imprecision, but these can be characterized and then harmonized to minimize the variation it contributes to measurements (6). Simplicity of collection, transport, and storage makes DBS samples an economical preference for many clinical applications. However, poor-quality filter paper and improperly collected DBS may significantly alter the performance of …

Background The Patient Perception of Patient-Centeredness (PPPC) questionnaire was revised, and there is a need for the questionnaire to be tested in diverse primary care populations. Objectives This study aimed to examine the factor structure of the Revised PPPC questionnaire (PPPC-R) in French-speaking patients with multimorbidity. Design Secondary analysis from baseline data of the French arm of Patient-Centered Innovations for Persons with Multimorbidity Study (PACEinMM Study). Setting and participants Participants were adult patients with multimorbidity attending primary health-care settings. Outcome measures Exploratory factor analyses were applied to examine the factor structure of the PPPC-R. Cronbach's alpha values were calculated to assess the internal consistency of the whole questionnaire and of each factor explored. Results There were 301 participants, mean age 61.0, 53.2% female. The PPPC-R showed very good internal consistency, with three factors: Patient-Centered Clinical Method (PCCM) Component 1-Exploring the health, disease and illness experience + PCCM Component 4-Enhancing the patient-clinician relationship (Factor 1); PCCM Component 2-Understanding the whole person (Factor 2); and PCCM Component 3-Finding common ground (Factor 3). There was a good internal consistency within each factor (Cronbach's α = 0.87 for 8 items in Factor 1, 0.77 for 5 items in Factor 2 and 0.87 for 5 items in Factor 3). Discussion and conclusions The French PPPC-R factor structure was in accordance with the underpinning conceptual model and presented with three factors. Further assessment of its validity and reproducibility are needed to allow its use as a measure of patient's perception of patient-centeredness.

Introduction The morbidity of chronic pancreatitis (CP) remains at a high level. In cases of CP, prepapillary stenosis of the common bile duct (CBD) complicates the course of disease in 30-60% of patients. Aim To improve the detection of biliary hypertension (BH) in patients with complicated forms of CP by increasing the accuracy of preoperative and intraoperative diagnostics using modern diagnostic methods. Material and methods We analysed the results of surgical treatment of 573 patients with complicated forms of CP. In 163 (28.5%) patients, CP was complicated by BH. The method of intraoperative monitoring of biliary pressure (IOM BP) was developed and introduced for intraoperative control and determination of the adequacy of intervention regarding biliary decompression. Results Mechanical jaundice was diagnosed by clinical methods in 101 (61.9%) CP patients with BH, and by laboratory methods in 108 (66.2%) patients. Such methods as magnetic resonance cholangiopancreatography (95.6%), endoscopic retrograde cholangiopancreatography (93.7%), and computed tomography (93.8%) proved to have the highest sensitivity for the diagnostics of BH in cases of CP. Conclusions The application of an integrated approach with extensive use of modern non-invasive preoperative methods of assessment allowed an approximation of the reliability of preoperative diagnostics of BH in CP patients to 95.6%. The use of the IOM BP method enables us to increase the sensitivity of intraoperative diagnostics of BH to 97.3% and choose the method of surgical intervention, which significantly reduces the risk of BH recurrence in the distant postoperative period by 15.1% (χ2 = 4.22, p = 0.04).

Coronary heart disease (the presence of coronary atherosclerotic plaques) is a significant health problem in the industrialized world. A clinical method to accurately visualize and characterize atherosclerotic plaques is needed. Intravascular photoacoustic (IVPA) imaging is being developed to fill this role, but questions remain regarding optimal imaging wavelengths. We utilized a Monte Carlo optical model to simulate IVPA excitation in coronary tissues, identifying optimal wavelengths for plaque characterization. Near-infrared wavelengths (≤1800 nm) were simulated, and single- and dual-wavelength data were analyzed for accuracy of plaque characterization. Results indicate light penetration is best in the range of 1050 to 1370 nm, where 5% residual fluence can be achieved at clinically relevant depths of ≥2 mm in arteries. Across the arterial wall, fluence may vary by over 10-fold, confounding plaque characterization. For single-wavelength results, plaque segmentation accuracy peaked at 1210 and 1720 nm, though correlation was poor (

Purpose The purpose of this article is to describe the appearance of age-related macular degeneration (AMD) phenotypes using infrared (IR) reflectance imaging. IR reflectance imaging of the retina has the potential to highlight specific sub-retinal features and pathology. However, its role in macular disease, specifically AMD, is often underestimated and requires clarification. Recent findings Recent advances in clinical methods, imaging and scientific knowledge may be integrated to improve the accuracy of disease stratification in AMD. In particular, IR imaging holds an underutilised sensitivity to detect reticular pseudodrusen, which have been repeatedly described as a high-risk sign for late AMD. Summary This article provides clinically relevant descriptions of AMD phenotypes using IR reflectance imaging. The findings are integrated with images from cases seen at the Centre for Eye Health. As primary eye-care providers assume a critical role in the detection, diagnosis and management of AMD, we also provide a chair-side reference to assist clinicians in interpreting IR images in AMD.

This paper offers the first examination of Archigenes of Apamea’s use of pain as a diagnostic method. Archigenes claimed that the kind of pain can indicate the affected part in the patient’s body and thus aid in successfully diagnosing and treating the patient. He listed the kinds of pains associated with different organs and used over thirty different terms to qualify pain, among these “numb”, “adherent” and “salty”. Archigenes’ terminology is usually considered incoherent and hence his method impractical. This paper argues that there was a solid foundation guiding Archigenes’ terminology and method. It claims that they rested on an inclusive conception and identification of pain, which took into account other sensations and physical phenomena which the patient was experiencing or the physician himself was observing. In so doing, Archigenes’ method gave the physicians a more active role in identifying and representing patients’ pain and released them from complete dependence on the patients and their subjective and often unreliable pain narratives. Revealing the foundation of Archigenes’ method brings to light an additional manner of conceptualising and narrating pain in the ancient world.

Uterine contractions monitoring is essential during pregnancy progression for due date prediction and the screening of preterm deliveries, i.e., those related to labour contractions occurring before 37 weeks of gestation. As there are different kinds of uterine contraction, distinguishing between true labour ones and normal physiological ones during pregnancy is not trivial. Thus, early identification is necessary for the effective and efficient care of pregnant women to avoid unnecessary and costly hospitalization. In this regard, while classical clinical methods proved their limitations, real-time monitoring of uterine contractions is now possible thanks to a new technique called ElectroHysteroGraphy which measures the uterine electrical activity that is a proxy for the mechanical activity of the muscles of the uterus. An exhaustive and comprehensive literature review was conducted to retrieve and report the state-of-the-art of the methods to distinguish labour contractions from pregnancy contractions. A systematic search was run on different search engines using a search string. A snowball sampling approach was applied to the references of the retrieved articles to identify further appropriate papers. According to this, the relevant references included in the bibliography of each analysed article led to other appropriate articles. Thus, papers dealing with the methods to distinguish labour from pregnancy (normal physiological) contractions and published between 2001 and 2020 were selected. Linear and nonlinear methods have been developed for uterine contractions signals (EHG/EMG) analysis to distinguish labour from pregnancy contractions. Nonlinear methods yielded better results compared to the linear methods, but not all nonlinear methods are promising in terms of clinical application.

Resumo: Neste texto discute-se os critérios utilizados pelas crianças dos anos iniciais referentes à função do acento gráfico no sistema de escrita. Considerando-se a estreita relação entre o acento prosódico e as regras de uso do acento gráfico pretendeu-se investigar as hipóteses das crianças em relação a este dispositivo ortográfico. Os dados analisados foram coletados a partir de um instrumento de escrita controlada criado especialmente para a pesquisa e de entrevistas orientadas pelo método clínico piagetiano (CARRAHER, 1989). Após a produção escrita as crianças foram provocadas, a fim de que explicitassem os motivos pelos quais utilizaram ou não o diacrítico em suas grafias. A análise dos dados de produção escrita mostra que as crianças acertam a grafia do acento preferencialmente nos contextos em que pode ocorrer a alternância de timbre da vogal tônica, ou seja, nas vogais médias e médias baixas. Os resultados das entrevistas apontam para a emergência de critérios baseados em correlatos acústicos e, também, em correlatos gráficos. Foi possível com a análise realizada definir uma hierarquia de critérios acústicos, a saber: timbre vocálico, duração e proeminência acentual. Abstract: This paper discusses the criteria used by third and fifth graders who attend a public school, in Pelotas, RS, Brazil, regarding the function of diacritical marks in the writing system. Considering the close relationship between prosodic stress and the rules of use of diacritical marks, the study reported in this paper aimed at investigating children's hypotheses concerning these orthographic devices. Data were collected by a controlled writing instrument, which was especially designed for this research, and by clinical interviews guided by the Piagetian method (CARRAHER, 1989). After completing a writing task, children were induced to explain the reasons that led them to use diacritics in their spelling. The analysis of data on their written production showed that children got the diacritical mark right, mainly in contexts in which alternation of vowel timbre could occur, that is, in medium and low medium vowels. Results of the interviews highlighted the emergence of criteria based on acoustic and graphic aspects. The analysis allowed us to define a hierarchy of acoustic criteria, i. e., vocalic timbre, vowel duration and prominence.

Enophthalmos has many causes, and serious post-traumatic cases indicate the need for operation. Such diagnoses should be made objectively, and a robust method for quantifying the degree to which the globe has been displaced is key. Current methods of measurement, however, have long been considered unreliable and inconsistent, in particular with regard to interobserver variability. The aim of this paper therefore was to review all these methods systematically, to analyse their reliability, and to compare them with others. The paper also includes a proposed protocol for the accurate and reliable measurement of protrusion of an eye, which aims to standardise the assessment of patients and to create a uniform approach that will enable the selection of those who are most likely to benefit from surgical treatment. Analysis of the data showed that computed tomographic (CT) exophthalmometry is the most reliable, followed by the Mourits' exophthalmometer, which performed better than the other clinical methods. In the acute phase of orbital blowout fractures, the measurement of herniated tissue through a fracture defect may give a good prediction of the degree of enophthalmos that is likely to occur without surgical correction. Measurement of the herniated volume and CT exophthalmometry should be the foundation for diagnosis and the planning of treatment. Three-dimensional imaging or Mourits' exophthalmometers (which are reliable non-radiological methods) could be used in a follow-up protocol.

This paper shows the importance of university extension projects for the effectiveness of sustainable campi to generate benefits for institutions and students from the social and environmental perspective. Having that in mind, the case study used is the role played by Clinica de Direito Ambiental Paulo Nogueira Neto (CPaNN), an environmental law clinic placed at University of Sao Paulo Law School. Initially, it is presented a historical and organizational overview of CPaNN, followed by the demonstration of CPaNN’s most concrete achievements, such as the installation of a bicycle rack in FDUSP’s building and the realization of educational campaigns concerning healthy habits and respect to work environment. Besides that, it concludes by demonstrating the relation between CPaNN’s activities as an example of the importance of activities of Education and Public Outreach and the concretization of more sustainable university spaces. It is perceived that the positivity of these actions accumulate experiences both for their receptors (university itself and individual campaigns targets) and for their actors as well (the students involved). This is an important paper because it illustrates successful cases of sustainability projects within the university; it hopes to offer a model for other institutions, whilst being open to discussion and yearning for improvement. The method used is descriptive-inductive with exploratory goals, using the authors’ own experience as the source of most of the information presented.

The bone age of a child indicates the skeletal and biological maturity of an individual. The most commonly applied clinical methods for Bone Age Assessment (BAA) are based on the visual examination of ossification of individual bones in radiographs of the left hand and the wrist by comparing with standard hand atlas. This kind of method is highly subjective and the performance extremely depends on practitioners' experiences. This paper investigates the use of Deep Convolutional Neural Networks (DCNNs) for the automatic bone age assessment. As there exists no large-scale annotated medical image dataset comparable to ImageNet for medical image analysis, this paper uses transfer learning within DCNNs to perform bone age classifications making full use of advantages of DCNNs. We define various Regions of Interest (ROIs) based on domain knowledge, for each of which a local bone age classification model is achieved by fine-tuning the pre-trained VGGNet with corresponding ROI patches. A final bone age classification is obtained by fusing multiple regional models. The results show that the proposed approach outperforms the current state-of-the-art classification methods in BAA with small dataset.

Human voice as well as the sound of the body is used as a clinical method to assess the health condition of an individual. The evaluation of the human voice has risen as a critical field of exploration. Speech analysis fundamentally involves the extraction of certain features from voice signals for generation of voice in alluring pertinence by using reasonable techniques. This paper brings up normal ailments that sway understanding voice patterns in proof for driving research that have affirmed voice modifications as demonstrative manifestations in their respective ailments and also the technique by which voice analysis can be done.

Chagas disease is one of the most important parasitic diseases transmitted to animals and people by insect vectors. According to the World Health Organization, around seven million people were infected with Trypanosoma cruzi (also known as kissing bug) that causes Chagas disease. As kissing bugs belong to different families with different danger levels, accurate classifications of kissing bugs species would help the public authorities create a controlled surveillance system. Clinical methods for detecting kissing bugs are expensive, time-consuming, and need a high level of expertise. To overcome these limitations, computational methods can be used. In this paper, a fully automated deep learning model using a convolutional neural network (CNN) with a fine-tuned transfer learning model is proposed to identify kissing versus non-kissing bugs and classify the type of kissing bug species. The accuracy of 99.45% for the classifications of kissing vs. non-kissing bugs and 96% for the classifications of different kissing bugs species is achieved. Finally, a web application is developed based on the proposed model to help the community collecting and identifying kissing bugs species.

Development of a chromatographic method in bioanalysis is a challenging and complex procedure with many pitfalls and often unexpected reversals that can require several months to accomplish. Even an experienced analytical team must contend many limitations mainly in connection with the strict requirements imposed on current clinical research. These restrictions typically persist throughout the whole development process, from clinical trial assignment, across optimization of extraction of biological materials and chromatographic separation, to validation and data interpretation. This paper describes questions and their possible answers raised during the pre-analytical phase such as use of modern sample preparation techniques in clinical methods, application of internal standards, as well as selection of stationary phases and detection techniques in the analytical phase. Validation problems and interpretation of results are demonstrated with three typical examples of characteristics to be considered, i.e. recovery, matrix effect, and limit of detection vs. lower limit of quantification.

The current paper introduces a clinical method for experience-near interpretation of transference patterns taking place in the symptom context. This research is a qualitative metasynthetic study. The method of Luborsky’s Core Conflictual Relationship Themes was conducted here on 33 transference case studies published in peer-reviewed journals and sourced from an appropriate database. Case components were categorized and relationships between them were analyzed using the method of Relationship Between Categories. We found that transferential components observed in the context of the symptom were a powerful source of distress. These components were found to be interlinked in patterns of two, three or four core categories. Based on these findings we suggest a therapeutic method that enhances self-understanding and maps out milestones for change. The suggested method is sensitive to a set of the patients’ covert associations, which thus becomes a key to undermining the unconscious balance between healthy and pathologic urges.

Pressure injury (PI) is a major problem for patients that are bound to a wheelchair or bed, such as seniors or people with spinal cord injuries. This condition can be life threatening in its later stages. It can be very costly to the healthcare system as well. Fortunately with proper monitoring and assessment, PI development can be prevented. The major factor that causes PI is prolonged interface pressure between the body and the support surface. A possible solution to reduce the chance of developing PI is changing the patient’s in-bed pose at appropriate times. Monitoring in-bed pressure can help healthcare providers to locate high-pressure areas, and remove or minimize pressure on those regions. The current clinical method of interface pressure monitoring is limited by periodic snapshot assessments, without longitudinal measurements and analysis. In this paper we propose a pressure signal analysis pipeline to automatically eliminate external artefacts from pressure data, estimate a person’s pose, and locate and track high-risk regions over time so that necessary attention can be provided.

Women with metastatic breast cancer (MBC) face serious physiological and psychosocial challenges. The management of this chronic, incurable condition requires long-term care coordination. Traditional clinical methods do not often provide adequate and personalized support for these individuals. In this project, we aim to use smart speakers to provide supportive care interventions to improve the quality of life for women with MBC. Specifically, we have developed Nurse AMIE (Addressing Metastatic Individuals Everyday) by leveraging the Amazon Alexa to remotely deliver validated interventions. We believe that voice interactions can significantly lower the barrier to interact with remote intervention technologies for this population. In a pilot study, we deployed Nurse AMIE for 14 days over 6 women with MBC. Based on the collected data, this paper discusses the feasibility, acceptability, and future directions of Nurse AMIE. To the best of our knowledge, this is the first study to use smart speakers to support women with MBC.

The advancement in the materials manufacturing at micrometer and nanometer scales has already enabled numerous applications in electronics, optics, chemistry, biology and medicine. Biomedical devices carrying micro-/nanostructures are currently being widely used in drug delivery, drug release, biosensing and therapy. New clinical methods for disease diagnosis and treatments are being developed enabled by nanotechnology. One-dimensional (1D) structures are playing an important role in the direct drug delivery both in vivo and ex vivo among various micro-/nanostructures. Here, in this paper, we reviewed recent progresses made on next-generation intradermal and intracellular delivery strategies and applications with focus on 1D microstructure-based approaches.

Liver cancer is the common malignant tumor in China and current treatment is based on surgery. However, liver function of many liver cancer patients is impaired before surgery, so there’s a high possibility of occurrence of liver failure after the tumor resection. Therefore, it’s necessary to accurately evaluate liver function before surgery. Currently, clinical methods are mostly limited to assess the function of overall liver. But the application of hepatocyte-specific contrast agent—gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) makes it possible to assess the function of local liver segment accurately. This paper reviewed the progress of using Gd-EOB-DTPA dynamic contrast enhanced magnetic resonance imaging (MRI) to assess liver function preoperatively, such as parameters selection for liver function assessment, clinical factors affecting Gd-EOB-DTPA enhanced MRI and so on.

There is now an extensive and highly developed literature within psychoanalysis on how best to understand the patients we work with, and their impact on the analyst or therapist, but far less on the mind of the clinician and how he or she thinks while working with the patient. One method for studying this, the Comparative Clinical Method developed by a group of European psychoanalysts, consists of a two step model: after a careful description of the interventions made by the analyst, an attempt is made to construct what is taken to be the analyst’s implicit working model, the internal template which he or she tacitly employs to conduct the analysis. In this paper I describe this model, which I then illustrate by taking a piece of published clinical material to show what an approach based on the Comparative Clinical Method might look like. Finally I make some comments on applying this model to the work of psychoanalytic psychotherapists.

Suicide is a critical issue in modern society. Early detection and prevention of suicide attempts should be addressed to save people's life. Current suicidal ideation detection methods include clinical methods based on the interaction between social workers or experts and the targeted individuals and machine learning techniques with feature engineering or deep learning for automatic detection based on online social contents. This paper is the first survey that comprehensively introduces and discusses the methods from these categories. Domain-specific applications of suicidal ideation detection are reviewed according to their data sources, i.e., questionnaires, electronic health records, suicide notes, and online user content. Several specific tasks and datasets are introduced and summarized to facilitate further research. Finally, we summarize the limitations of current work and provide an outlook of further research directions., IEEE Transactions on Computational Social Systems

International audience; Diabetic retinopathy (DR) is the most common eye complication of diabetes and one of the leading causes of blindness and vision impairment. Automated and accurate DR grading is of great significance for the timely and effective treatment of fundus diseases. Current clinical methods remain subject to potential time-consumption and high-risk. In this paper, a hierarchically Coarse-to-fine network (CF-DRNet) is proposed as an automatic clinical tool to classify five stages of DR severity grades using convolutional neural networks (CNNs). The CF-DRNet conforms to the hierarchical characteristic of DR grading and effectively improves the classification performance of five-class DR grading, which consists of the following: (1) The Coarse Network performs two-class classification including No DR and DR, where the attention gate module highlights the salient lesion features and suppresses irrelevant background information. (2) The Fine Network is proposed to classify four stages of DR severity grades of the grade DR from the Coarse Network including mild, moderate, severe non-proliferative DR (NPDR) and proliferative DR (PDR). Experimental results show that proposed CF-DRNet outperforms some state-of-art methods in the publicly available IDRiD and Kaggle fundus image datasets. These results indicate our method enables an efficient and reliable DR grading diagnosis in clinic.

Falls affect a growing number of the population each year. Clinical methods to identify those at greatest risk for falls usually evaluate individuals while they perform specific motions such as balancing or Sit-to-Stand (STS). Unfortunately these techniques have been shown to have poor predictive power and are unable to identify the magnitude, direction, and timing of perturbations that can cause an individual to lose stability during motion. To address this limitation, the recently proposed Stability Basin (SB) aims to characterize the set of perturbations that will cause an individual to fall under a specific motor control strategy. The SB is defined as the set of configurations that do not lead to failure for an individual under their chosen control strategy. This paper presents a novel method to compute the SB and the first experimental validation of the SB with an 11-person perturbative STS experiment involving forwards or backwards pulls from a motor-driven cable. The individually-constructed SBs are used to identify when a trial fails, i.e., when an individual must switch control strategies (indicated by a step or sit) to recover from a perturbation. The constructed SBs correctly predict the outcome of trials where failure was observed with over 90% accuracy, and correctly predict the outcome of successful trials with over 95% accuracy. The SB was compared to three other methods and was found to estimate the stable region with over 45% more accuracy in all cases. This study demonstrates that SBs offer a novel model-based approach for quantifying stability during motion, which could be used in physical therapy for individuals at risk of falling., 19 pages, 9 figures

For patients with major burn injuries, an accurate burn size estimation is essential to plan appropriate treatment and minimize medical and surgical complications. However, current clinical methods for burn size estimation lack accuracy and reliability. To overcome these limitations, this paper proposes a 3D-based approach—with personalized 3D models from a limited set of anthropometric measurements—to accurately assess the percent TBSA affected by burns. First, a reliability and feasibility study of the anthropometric measuring process was performed to identify clinically relevant measurements. Second, a large representative stratified random sample was generated to output several anthropometric features required for predictive modeling. Machine-learning algorithms assessed the importance and the subsets of anthropometric measurements for predicting the BSA according to specific patient morphological features. Then, the accuracy of both the morphology and BSA of 3D models built from a limited set of measurements was evaluated using error metrics and maximum distances 3D color maps. Results highlighted the height and circumferences of the bust, neck, hips, and waist as the best predictors for BSA. 3D models built from three to four anthropometric measurements showed good accuracy and were geometrically close to gold standard 3D scans. Outcomes of this study aim to decrease medical and surgical complications by decreasing errors in percent TBSA assessments and, therefore, improving patient outcomes by personalizing care.

RESUMO: O presente trabalho aborda a temática do método clínico na pesquisa em psicanálise, a partir da experiência de atendimento de um adolescente desde a perspectiva do Acompanhamento Terapêutico (AT). Tomando a pesquisa em psicanálise como uma produção marcada pela indissociabilidade entre saber teórico e prática clínica, discutiremos o método da construção do caso clínico, entendida como uma ficção produzida pelo encontro que a clínica promove. Apresentaremos, nesse contexto, a experimentação de uma “escrita compartilhada” com o adolescente acompanhado, abrindo a possibilidade de que ele escreva, reescreva e ressignifique a sua própria história, produzindo, assim, novos sentidos para si. ABSTRACT: This paper introduces the subject-matter of the clinical method in psychoanalytic research, discussing the treatment experience of a teenager boy by the perspective of the Therapeutic Accompaniment (TA). Taking research in psychoanalysis as a production marked by the integration between theoretical knowledge and clinical practice, we discuss the method of construction of the case, understood as a fiction produced by the encounter that clinical promotes. We will present, in this context, the trial of a “writing shared” with the accompanied teenager, opening the possibility for him to write, rewrite and reframe his own history, thereby producing new meanings for himself.

Introduction: The application of the patient-centered clinical method (PCCM) aims to achieve the understanding about the patient and his/her condition by means of the approach from two perspectives: the doctor’s and the patient’s. The satisfaction of the users is considered as a major indicator of service evaluation. Purpose: This paper aims to investigate whether there is an association between the degree of PCCM orientation, according to the patient’s perception, and the satisfaction with the most recent medical appointment in a primary health care (PHC) service. Methods: This is a cross-sectional study, developed with hypertensive and/or diabetic patients in the 12 health care centers of a PHC service in Porto Alegre, RS (n = 408). The degree of PCCM orientation was measured by the use of the “Patient Perception of Patient-Centeredness” (PPPC) tool. Results: The low general score of the PPPC (corresponding to the high PCCM orientation) was significantly associated with the higher satisfaction of the patients with aspects related to the service (scheduling mode and cordiality at the reception) and the medical care (attention paid to the demands by the doctor, physical exam by the doctor, explanations about the problem, and explanations on the prognosis), the appointment in general, and to the systemic hypertension and/or diabetes mellitus treatment in the health care center. Discussion: The PHC doctor must be more person-oriented to achieve, therefore, higher levels of satisfaction. In this perspective, the incorporation of the users’ satisfaction in the evaluation of health services must be a quality indicator, especially of the approach practiced by the doctor.

Neurogenic neoplasms resulting from autonomic nerves are considerably rare. In this paper, we report a case of a 41-year-old woman with composite tumor of synchronous ganglioneuroma and schwannoma in the vagal inferior ganglion. Ultrasonography and computed tomography showed a well-defined mass, which extruded from the internal and external carotid arteries. Two tumors were closely attached but with an evident boundary. The small tumor was composed of spindle cells and numerous mature ganglion cells, and the large one consisted entirely of differentiated neoplastic Schwann cells. Results showed that these tumors were a schwannoma arising in a ganglioneuroma of the vagal inferior ganglion. Our case is the first to demonstrate the occurrence of schwannoma in benign ganglioneuroma. We also provided clinical and pathological evidence that such transformation can occur spontaneously. .

This paper analyzes the internal mechanisms of the individual positive and negative attitude towards appearance, the description of which is under-represented in the psychological literature. The process of creating a consistent image of the physical «Self» and maintaining a positive emotional evaluation of the body and appearance particularly seen through the idea of assigning the individual components of appearance, committed throughout the whole course of life, and is understood as a specific psychological problem, addressable only in human personality as integrative unity, preserving and maintaining its integrity. The hypothesis of the study made by the assumption that a positive attitude to their external appearance is ensured, actualization processes semantic and symbolic mediation of the physical and expressive features, and on the contrary, a negative attitude toward the appearance indicates the failure of such processes. The following characteristics of body image were considered: emotional assessment and the nature of the work on the body, the internal means of maintaining a positive attitude to their appearance, and also the broader context of personal characteristics, particularly the motivational sphere, psychological defenses, the general harmony, integration of personality structure. Differences were demonstrated between conscious and unconscious relation to the external appearance among the subjects, presented significant correlations between the non-integration of personal organization and the negative attitude towards appearance, and between the presence of supervaluation group needs and the negative assessment by the subjects of their appearance. The subjects who accept their appearance are characterized by a greater representation of mediation systems as the assignment of funds in the structure of the physical image «Self», as compared to subjects not receiving their physical appearance.

International audience; Automatic and accurate esophageal lesion classification and segmentation is of great significance to clinically estimate the lesion statuses of the esophageal diseases and make suitable diagnostic schemes. Due to individual variations and visual similarities of lesions in shapes, colors, and textures, current clinical methods remain subject to potential high-risk and time-consumption issues. In this paper, we propose an Esophageal Lesion Network (ELNet) for automatic esophageal lesion classification and segmentation using deep convolutional neural networks (DCNNs). The underlying method automatically integrates dual-view contextual lesion information to extract global features and local features for esophageal lesion classification and lesion-specific segmentation network is proposed for automatic esophageal lesion annotation at pixel level. For the established clinical large-scale database of 1051 white-light endoscopic images, ten-fold cross-validation is used in method validation. Experiment results show that the proposed framework achieves classification with sensitivity of 0.9034, specificity of 0.9718, and accuracy of 0.9628, and the segmentation with sensitivity of 0.8018, specificity of 0.9655, and accuracy of 0.9462. All of these indicate that our method enables an efficient, accurate, and reliable esophageal lesion diagnosis in clinics.

Dry eye disease (DED) is a multifactorial condition of the tear and ocular surface that is characterized by loss of homeostasis and symptoms of tear instability. Some symptoms of DED include blurring of vision, crusting of eyelids, and irritation to the eyes. An array of clinical methods, such as Schirmer’s test, is used to classify DED. Yet, these approaches are often invasive, need to be performed manually by clinicians, and/or they do not have reproducible results. They are also prone to interobserver variation among clinicians. Thus, computer-aided detection (CAD) systems are preferred for DED diagnosis. This paper reviews the existing CAD techniques used to automatically diagnose DED, and focuses on the benefits of thermographic CAD systems. CAD systems for DED using thermography are found to be highly sensitive, specific, accurate, minimally invasive, convenient, and satisfactory. Also, deep learning techniques are discussed to precede conventional machine learning techniques in the development of a CAD system. It is concluded that the use of thermographic CAD systems coupled with a deep learning technique is likely to be useful for DED assessment in future work.

Advances in medical device engineering, as well as our continuously increasing understanding of brain function, has increased the safety, reliability, and efficacy of neuromodulation methods for regulating human behavior over the past couple decades. Clinical neuromodulation devices are becoming frequently used for treating neurological and psychiatric disorders. Most clinical methods however rely on surgically implanted electrodes, such as those incorporated by deep-brain stimulation systems to treat Parkinson’s disease. Several different methods of noninvasive neuromodulation also exist and have been used to alter brain activity for research applications or to treat some nervous systems disorders. Some noninvasive methods involve delivering electrical currents or electromagnetic pulses to specific peripheral nerves or brain targets in order to modulate nervous system activity. Other more recently developed methods use focused ultrasound to noninvasively modulate human brain circuits or nerves at high spatiotemporal resolutions. Beyond the utility of restoring loss of function in therapeutic embodiments, these safety benchmarks have encouraged the widespread investigation of several different types of neuromodulation methods for their potential to increase gains in the performance and function of healthy individuals. Noninvasive neuromodulation has been shown to enhance brain plasticity and physical performance, accelerate learning, increase attention, and improve sleep. Additive gains have been shown when combining neuromodulation devices with biosensors and virtual immersion gaming systems as human computer interfaces. An overview of how electrical and ultrasonic neuromodulation methods embodied as human computer interfaces are being developed for enhancing the performance of military operators and defense personnel is provided in the present paper.

Dengue virus is a growing problem in tropical countries. It serves disease, especially in children. Some exiting clinical methods CIMSiM, DENSiM, ELISA, SPSS, SARIMA, PCR and RT-PCR need a volume of blood cells which cannot be obtained from children. Meanwhile, some existing machine learning algorithms are used to diagnose the dengue infection based on the date of dengue fever, days, current temperature, white blood cell count, joint muscles, metallic taste in mouth, appetite, abdomen pain, hemoglobin, mild bleeding, vomiting, headaches, rainfall, and relative humidity attributes. These methods are used to diagnose the dengue in later stages. Sometimes these methods could not identify the correct results. To overcome these problems, this paper proposes the stable method of classifying dengue serotypes based on amino acids in the protein sequences. It needs only skin cells or hair or nail which can be easily obtained from any person including children also. The proposed method classifies dengue serotypes using entropy-based feature selection and rule extracted from the neural network. Results of the experiments show that the proposed method for classifying dengue fevers with its serotypes.

The selection of athletes has been a central topic in sports sciences for decades. Yet, little consideration has been given to the theoretical underpinnings and predictive validity of the procedures. In this paper, we evaluate current selection procedures in sports given what we know from the selection psychology literature. We contrast the popular clinical method (predictions based on overall impressions of experts) with the actuarial approach (predictions based on pre-defined decision rules), and we discuss why the latter approach often leads to superior performance predictions. Furthermore, we discuss the “signs” and the “samples” approaches. Taking the prevailing signs approach, athletes’ technical-, tactical-, physical-, and psychological skills are often assessed separately in controlled settings. However, for predicting later sport performance, taking samples of athletes’ behaviours in their sports environment may result in more valid assessments. We discuss the possible advantages and implications of making selection procedures in sports more actuarial and sample-based.

Statement of problem A valid system for assessing and classifying functional occlusion has not been established. The prevalence of anterior protected articulation is not known. Purpose The purpose of this study was to quantify the prevalence of various functional occlusal contact patterns, including anterior protected articulation, among dental students. Material and methods Occlusal contacts were examined during lateral excursions from the maximal intercuspal position to the canine-to-canine position in 100 young adults. A combination of 3 common clinical methods was used: a visual examination, articulating paper, and feedback from the participants. Results Data from 3 classification systems were analyzed: (1) Occlusal contacts on the working side only – canine protected articulation was present in 25% of laterotrusions; anterior protected articulation was present in 18.5% of laterotrusions. Group function was present in 56% of laterotrusions. Other schemes were present in 0.5% of laterotrusions. (2) Contacts on both the working and the nonworking side. (3) Contacts on the working and nonworking side during both right and left laterotrusion. Nonworking side contacts were present in 33% of the participants. Nonworking side interference was present in 1 participant. Conclusions The prevalence of anterior protected articulation found in this study was high enough to allow anterior protected articulation to be considered one of the fundamental working side occlusal contact patterns. More studies will be necessary to confirm this finding.

Therapeutic hypothermia (TH) is an important treatment for post-cardiac arrest syndrome. Despite its widespread practice, only limited data describe the thermodynamic aspects of heat transfer during TH. This paper reviews the principles of human body heat balance and provides a conceptual model for characterizing heat exchange during TH. The model may provide a framework for computer simulation for improving training in or clinical methods of TH.

Ankle sprain Injury is one of the most common ankle injuries due to domestic or sporting accidents. There is a need for greater demand for quick and effective ankle rehabilitation system (ARS). Nowadays, research on ARS has gained a great attention than manual clinical method in medical areas such as orthopedic injuries, pediatrics sport medicine and industrial services. It can improve the treatment conditions by reducing the dependency of doctors’ supervision, help patient with less movable to have home-based rehab exercise and help to speeds up recovery. There are currently available ARS that can provide effective ankle rehabilitation treatment such as Visual, Non-Visual and Robot-aided. In this paper, the critical review of ARS is conducted to evaluate the effectiveness of ARS in terms of provided setting criteria. The strengths, weaknesses, opportunities and threats of each ARS is discussed and compared to identify the most suitable home application of ARS for ankle sprain patient. From the comparison, the most suitable home application ARS is the visual marker-less based ARS system which give user-friendly, efficiency, validity in performance and cheaper cost.

Body auscultation one of the main common clinical diagnostic technique for assessment of cardiac disorders. This clinical method is cheap and effective and requires professional doctors to understand and interpret the heart sound for diagnosis of cardiac diseases. This paper presents basic analysis and comparison of heart sounds recorded from healthy and unhealthy subjects for automated screening of cardiac disorders. Some characteristics of heart sounds such as probability distribution of amplitude and frequency contents are quantified using signal processing to automate the diagnosis of cardiac disorders. Experiments were carried on the Heart sounds database created under National Institute of Health (National Center for Research Resources) and results are encouraging. The experiment results indicates enough discrimination between heart sounds from healthy and unhealthy heart sounds for automated screening of cardiac disorders using signal processing.

Glaucoma is one of the leading causes of permanent vision loss. It is an ocular disorder caused by increased fluid pressure within the eye. The clinical methods available for the diagnosis of glaucoma require skilled supervision. They are manual, time consuming, and out of reach of common people. Hence, there is a need for an automated glaucoma diagnosis system for mass screening. In this paper, we present a novel method for an automated diagnosis of glaucoma using digital fundus images. Variational mode decomposition (VMD) method is used in an iterative manner for image decomposition. Various features namely, Kapoor entropy, Renyi entropy, Yager entropy, and fractal dimensions are extracted from VMD components. ReliefF algorithm is used to select the discriminatory features and these features are then fed to the least squares support vector machine (LS-SVM) for classification. Our proposed method achieved classification accuracies of 95.19% and 94.79% using three-fold and ten-fold cross-validation strategies, respectively. This system can aid the ophthalmologists in confirming their manual reading of classes (glaucoma or normal) using fundus images.

When performing tasks such as remembering letters, numbers, objects, or shapes, a persons Visual Sequential Memory (VSM) plays a crucial role, especially when the order of the tasks is important. Lack of VSM makes the persons life more challenging, possibly leading to dyslexia and dyscalculia. As such, it is important to detect and treat Visual Sequential Memory Deficit (VSMD). But current clinical methods have a low rate of diagnosis, and also offer limited hours to persons being treated in the clinics. In this paper, we propose an Origami based Serious Game, called Memori, as a synthetic instrument for the diagnosis, performance measurement, and treatment of people with VSMD. We illustrate the rationale behind using Origami, the design process of our game, and its implementation. Our preliminarily performance evaluations with 24 adults reveal a 13% improvement of memory and 1.00 score increase in performance while a slight decrease occurred in attentiveness from 2.33 to 2.02 for people who use our tool.

Visual Sequential Memory (VSM) allows a person to perform tasks such as remembering letters, numbers, objects or shapes in the correct order. Its deficit can lead to challenges in one's personal life, including dyslexia and dyscalculia. Detecting Visual Sequential Memory Deficit (VSMD) is essential for those who suffer from its related consequences. But current clinical methods don't have a high rate of diagnosis, and also for treatment are limited to the few hours the person spends in the clinic. In this paper, we propose an Origami based Serious Game, called Memori, for the diagnosis and treatment of children with VSMD. We illustrate the rationale behind using Origami, the design process of our game, and its implementation.