Glaucoma is the leading cause of irreversible blindness globally. Research indicates a disproportionate impact of glaucoma on racial and ethnic minorities. Existing deep learning models for glaucoma detection might not achieve equitable performance across…
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A guide to completing an EPA – Clinical Assessment.Learn more at www.digitalhealth.gov.au/healthcare-providers/initiatives-and-programs/workforce-capability/clinical-learning-australia…
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A guide to logging in to the CLA system and reviewing the settings that can be changed.More information can be found here: https://www.digitalhealth.gov.au/healthcare-providers/initiatives-and-programs/workforce-capability/clinical-learning-australia…
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Extensive research on retinal layer segmentation (RLS) using deep learning (DL) is mostly approaching a performance plateau, primarily due to reliance on structural information alone. To address the present situation, we conduct the first…
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Editor’s Note: This is part two of a two-part interview. To read part one, click here.Children’s National Hospital, in Washington, D.C., is making robust use of artificial intelligence technologies in both clinical and administrative…
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While machine learning (ML)-based solutions—often referred to as artificial intelligence (AI) solutions—have demonstrated comparable or superior performance to human experts across various healthcare applications, their vulnerability to perturbations and stability to variations due to…
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Machine learning has increasingly been applied to predict opioid-related harms due to its ability to handle complex interactions and generating actionable predictions. This review evaluated the types and quality of ML methods in opioid…
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This week Abridge announced that its artificial intelligence listening documentation platform will be distributed more broadly at Mayo Clinic to improve patient care following the health system’s evaluation. The use of Google’s and other’s…
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This systematic review explores machine learning (ML) applications in surgical motion analysis using non-optical motion tracking systems (NOMTS), alone or with optical methods. It investigates objectives, experimental designs, model effectiveness, and future research directions….
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Remote, digital cognitive testing on an individual’s own device provides the opportunity to deploy previously understudied but promising cognitive paradigms in preclinical Alzheimer’s disease (AD). The Boston Remote Assessment for NeuroCognitive Health (BRANCH) captures…
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