94,116 research outputs found

    Improving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

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    Confocal laser endomicroscopy (CLE), although capable of obtaining images at cellular resolution during surgery of brain tumors in real time, creates as many non-diagnostic as diagnostic images. Non-useful images are often distorted due to relative motion between probe and brain or blood artifacts. Many images, however, simply lack diagnostic features immediately informative to the physician. Examining all the hundreds or thousands of images from a single case to discriminate diagnostic images from nondiagnostic ones can be tedious. Providing a real-time diagnostic value assessment of images (fast enough to be used during the surgical acquisition process and accurate enough for the pathologist to rely on) to automatically detect diagnostic frames would streamline the analysis of images and filter useful images for the pathologist/surgeon. We sought to automatically classify images as diagnostic or non-diagnostic. AlexNet, a deep-learning architecture, was used in a 4-fold cross validation manner. Our dataset includes 16,795 images (8572 nondiagnostic and 8223 diagnostic) from 74 CLE-aided brain tumor surgery patients. The ground truth for all the images is provided by the pathologist. Average model accuracy on test data was 91% overall (90.79 % accuracy, 90.94 % sensitivity and 90.87 % specificity). To evaluate the model reliability we also performed receiver operating characteristic (ROC) analysis yielding 0.958 average for the area under ROC curve (AUC). These results demonstrate that a deeply trained AlexNet network can achieve a model that reliably and quickly recognizes diagnostic CLE images.Comment: SPIE Medical Imaging: Computer-Aided Diagnosis 201

    Evaluating tools to support a new practical classification of diabetes: excellent control may represent misdiagnosis and omission from disease registers is associated with worse control.

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    To conduct a service evaluation of usability and utility on-line clinical audit tools developed as part of a UK Classification of Diabetes project to improve the categorisation and ultimately management of diabetes

    Screening and assessment tools for gaming disorder: A comprehensive systematic review

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    The inclusion of gaming disorder (GD) as an official diagnosis in the ICD-11 was a significant milestone for the field. However, the optimal measurement approaches for GD are currently unclear. This comprehensive systematic review aimed to identify and evaluate all available English-language GD tools and their corresponding evidence. A search of PsychINFO, PsychArticles, ScienceDirect, Scopus, Web of Science, and Google Scholar identified 32 tools employed in 320 studies (N = 462,249 participants). The evaluation framework examined tools in relation to: (1) conceptual and practical considerations; (2) alignment with DSM-5 and ICD-11 criteria; (3) type and quantity of studies and samples; and (4) psychometric properties. The evaluation showed that GD instrumentation has proliferated, with 2.5 tools, on average, published annually since 2013. Coverage of DSM-5 and ICD-11 criteria was inconsistent, especially for the criterion of continued use despite harm. Tools converge on the importance of screening for impaired control over gaming and functional impairment. Overall, no single tool was found to be clearly superior, but the AICA-Sgaming, GAS-7, IGDT-10, IGDS9-SF, and Lemmens IGD-9 scales had greater evidential support for their psychometric properties. The GD field would benefit from a standard international tool to identify gaming-related harms across the spectrum of maladaptive gaming behaviors.Peer reviewedFinal Accepted Versio

    The influence of patient and doctor gender on diagnosing coronary heart disease

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    Using novel methods, this paper explores sources of uncertainty and gender bias in primary care doctors’ diagnostic decision making about coronary heart disease (CHD). Claims about gendered consultation styles and quality of care are re-examined, along with the adequacy of CHD models for women. Randomly selected doctors in the UK and the US (n=112, 56 per country, stratified by gender) were shown standardised videotaped vignettes of actors portraying patients with CHD. ‘Patients’ age, gender, ethnicity and social class were varied systematically. During interviews, doctors gave free-recall accounts of their decision making, which were analysed to determine patient and doctor gender effects. We found differences in male and female doctors’ responses to different types of patient information. Female doctors recall more patient cues overall, particularly about history presentation, and particularly amongst women. Male doctors appear less affected by patient gender but both male and especially female doctors take more account of male patients’ age and consider more age-related disease possibilities for men than women. Findings highlight the need for better integration of knowledge about female presentations within accepted CHD risk models, and do not support the contention that women receive better quality care from female doctors

    The prodrome of autism: early behavioral and biological signs, regression, peri- and post-natal development and genetics

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    Autism is one of the most heritable neurodevelopmental conditions and has an early onset, with symptoms being required to be present in the first 3 years of life in order to meet criteria for the ‘core’ disorder in the classification systems. As such, the focus on identifying a prodrome over the past 20 years has been on pre-clinical signs or indicators that will be present very early in life, certainly in infancy. A number of novel lines of investigation have been used to this end, including retrospective coding of home videos, prospective population screening and ‘high risk’ sibling studies; as well as the investigation of pre- and peri-natal, brain developmental and other biological factors. Whilst no single prodromal sign is expected to be present in all cases, a picture is emerging of indicative prodromal signs in infancy and initial studies are being undertaken to attempt to ameliorate the early presentation and even ‘prevent’ emergence of the full syndrome

    Influence of study design on digital pathology image quality evaluation : the need to define a clinical task

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    Despite the current rapid advance in technologies for whole slide imaging, there is still no scientific consensus on the recommended methodology for image quality assessment of digital pathology slides. For medical images in general, it has been recommended to assess image quality in terms of doctors’ success rates in performing a specific clinical task while using the images (clinical image quality, cIQ). However, digital pathology is a new modality, and already identifying the appropriate task is difficult. In an alternative common approach, humans are asked to do a simpler task such as rating overall image quality (perceived image quality, pIQ), but that involves the risk of nonclinically relevant findings due to an unknown relationship between the pIQ and cIQ. In this study, we explored three different experimental protocols: (1) conducting a clinical task (detecting inclusion bodies), (2) rating image similarity and preference, and (3) rating the overall image quality. Additionally, within protocol 1, overall quality ratings were also collected (task-aware pIQ). The experiments were done by diagnostic veterinary pathologists in the context of evaluating the quality of hematoxylin and eosin-stained digital pathology slides of animal tissue samples under several common image alterations: additive noise, blurring, change in gamma, change in color saturation, and JPG compression. While the size of our experiments was small and prevents drawing strong conclusions, the results suggest the need to define a clinical task. Importantly, the pIQ data collected under protocols 2 and 3 did not always rank the image alterations the same as their cIQ from protocol 1, warning against using conventional pIQ to predict cIQ. At the same time, there was a correlation between the cIQ and task-aware pIQ ratings from protocol 1, suggesting that the clinical experiment context (set by specifying the clinical task) may affect human visual attention and bring focus to their criteria of image quality. Further research is needed to assess whether and for which purposes (e.g., preclinical testing) task-aware pIQ ratings could substitute cIQ for a given clinical task
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