Depression in older adults is often underdiagnosed and has been linked to adverse outcomes, including motor vehicle crashes. With a growing population of older drivers in the United States, innovations in screening methods are…
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Distributed learning enables collaborative machine learning model training without requiring cross-institutional data sharing, thereby addressing privacy concerns. However, local quality control variability can negatively impact model performance while systematic human visual inspection is time-consuming…
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Applying machine learning to clinical outcome prediction is challenging due to imbalanced datasets and sensitive tasks that contain rare yet critical outcomes and where equitable treatment across diverse patient groups is essential. Despite attempts,…
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Musculoskeletal complaints account for 30% of GP consultations, with many referred to rheumatology clinics via letters. This study developed a Machine Learning (ML) pipeline to prioritize referrals by identifying rheumatoid arthritis (RA), osteoarthritis, fibromyalgia,…
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Proposed legislation introduced in the U.S. House of Representatives will allow AI and machine learning technology to prescribe drugs approved by the FDA autonomously. The bill, H.R.238, introduced on Jan. 7, would require amending the…
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Upper gastrointestinal cancer (UGC) sometimes metastasizes to the splenic hilum lymph node (SHLN). However, surgical removal of SHLN is technically difficult, and the risk of postoperative complications is high. Although there are models that…
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This study examines the relationship between self-reported and physiologically measured sleep quality and their impact on neurocognitive performance in individuals with depression. Using data from 249 participants with medium to severe depression monitored over…
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Antimicrobial resistance is a rising global health threat, leading to ineffective treatments, increased mortality and rising healthcare costs. In ICUs, inappropriate empiric antibiotic therapy is often given due to treatment urgency, causing poor outcomes….
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The European CORE–MD consortium (Coordinating Research and Evidence for Medical Devices) proposes a score for medical devices incorporating artificial intelligence or machine learning algorithms. Its domains are summarised as valid clinical association, technical performance,…
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This study demonstrates the potential of multimodal large language models in calculating safety indicators and predicting contraindications for laser vision correction. ChatGPT-4 effectively analyzed ocular data, calculated key indicators, generated calculator codes, and outperformed…
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