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Optimizing latent graph representations of surgical scenes for unseen domain generalization
PurposeAdvances in deep learning have resulted in effective models for surgical video analysis; however, these models often fail to generalize across...
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Automated classification of polyps using deep learning architectures and few-shot learning
BackgroundColorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all...
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Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review
Diabetes as a metabolic illness can be characterized by increased amounts of blood glucose. This abnormal increase can lead to critical detriment to...
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Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
Patients with COVID-19 and metabolic-dysfunction associated fatty liver disease (MAFLD) appear to be at higher risk for severe manifestations,...
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Automated bone marrow cytology using deep learning to generate a histogram of cell types
BackgroundBone marrow cytology is required to make a hematological diagnosis, influencing critical clinical decision points in hematology. However,...
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Drug knowledge discovery via multi-task learning and pre-trained models
BackgroundDrug repurposing is to find new indications of approved drugs, which is essential for investigating new uses for approved or...
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Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms
ObjectivesRisk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI...
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Educating the healthcare workforce of the future: lessons learned from the development and implementation of a ‘Wearables in Healthcare’ course
Digital health technologies will play an ever-increasing role in the future of healthcare. It is crucial that the people who will help make that...
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A deep learning approach to automatically quantify lower extremity alignment in children
ObjectiveTo develop and validate a convolutional neural network (CNN) capable of predicting the anatomical landmarks used to calculate the...
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Development of Medical Imaging Data Standardization for Imaging-Based Observational Research: OMOP Common Data Model Extension
The rapid growth of artificial intelligence (AI) and deep learning techniques require access to large inter-institutional cohorts of data to enable...
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Joint EANM/SNMMI guideline on radiomics in nuclear medicine
PurposeThe purpose of this guideline is to provide comprehensive information on best practices for robust radiomics analyses for both hand-crafted...
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Operationalizing Equity, Inclusion, and Access in Research Practice at a Large Academic Institution
IntroductionHealthcare advances are hindered by underrepresentation in prospective research; sociodemographic, data, and measurement infidelity in...
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Neurocognitive effects of stress: a metaparadigm perspective
Stressful experiences, both physical and psychological, that are overwhelming (i.e., inescapable and unpredictable), can measurably affect subsequent...
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Digital Media and Develo** Brains: Concerns and Opportunities
Purpose of ReviewThe incorporation of digital technologies and their use in youth’s everyday lives has been increasing rapidly over the past several...
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Surfing the COVID-19 Tsunami with Teleophthalmology: the Advent of New Models of Eye Care
Purpose of ReviewIn this article, we reviewed the impact resulting from the COVID-19 pandemic on the traditional model of care in ophthalmology.
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Technical Review of Clinical Outcomes Assessments Across the Continuum of Alzheimer's Disease
IntroductionInsight into the relationship between concepts that matter to the people affected by Alzheimer’s disease (AD) and the clinical outcome...
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Integrated multimodal artificial intelligence framework for healthcare applications
Artificial intelligence (AI) systems hold great promise to improve healthcare over the next decades. Specifically, AI systems leveraging multiple...
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Experienced based co design: nursing preceptorship educational programme
BackgroundPatients play a central role in nursing preceptorship relationships, a professional educational relationship between a staff nurse and...
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Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis
A robust medical image computing infrastructure must host massive multimodal archives, perform extensive analysis pipelines, and execute scalable job...
