Retinal photography is a valuable non-invasive tool for assessing vascular health, but genetic evidence linking retinal microcirculation to major vascular-related diseases (e.g., myocardial infarction [MI], stroke, and chronic kidney disease [CKD]) remains scarce. This…
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Rapid advances in large language models (LLMs) are transforming the role of students and principal investigators (PIs) in biomedical research. This perspective examines how LLMs can reshape the laboratory model as de facto “Co-PIs”…
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What You Should Know:
– The Centers for Medicare & Medicaid Services (CMS) today issued a proposed rule for the Calendar Year (CY) 2026 Medicare Physician Fee Schedule (PFS).
– The proposal aims to increase quality…
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Accurate and comprehensive interpretation of pulmonary embolism (PE) from Computed Tomography Pulmonary Angiography (CTPA) scans remains a clinical challenge due to the limited specificity and structure of existing AI tools. We propose an agent-based…
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We introduce a framework to adapt large language models for medicine: (1) Modeling: breaking down medical workflows into manageable steps; (2) Optimization: optimizing model performance via advanced adaptations; and (3) System engineering: developing agent…
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Credit: Campanella, et al., Nature Medicine
What You Should Know:
– A new study by researchers at the Icahn School of Medicine at Mount Sinai, Memorial Sloan Kettering Cancer Center, and collaborators, suggests that artificial intelligence…
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What You Should Know:
– Top U.S. health systems are taking bold, employer-led action to combat two converging crises: staggering student debt and critical clinical staffing shortages. Together with Clasp, the first retention-driven recruitment platform,…
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With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imaging can reassess the need for surgical axillary staging. This study employed advancements in deep learning to comprehensively evaluate routine mammograms for…
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Medical image segmentation is vital for accurate diagnosis. While U-Net-based models are effective, they struggle to capture long-range dependencies in complex anatomy. We propose GH-UNet, a Group-wise Hybrid Convolution-ViT model within the U-Net framework,…
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Endoscopic interventions are essential for diagnosing and treating gastrointestinal conditions. Accurate and comprehensive documentation is crucial for enhancing patient safety and optimizing clinical outcomes; however, adverse events remain underreported. This study evaluates a machine…
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