Large language models (LLMs) demonstrate significant potential in healthcare applications, but clinical deployment is limited by privacy concerns and insufficient medical domain training. This study investigated whether retrieval-augmented generation (RAG) can improve locally deployable…
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Immunohistochemistry (IHC) is crucial for the clinical categorisation of breast cancer cases. Deep generative models may offer a cost-effective alternative by virtually generating IHC images from hematoxylin and eosin samples. This review explores the…
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Target trial emulation (TTE) aims to estimate treatment effects by simulating randomized controlled trials using real-world observational data. Applying TTE across distributed datasets shows great promise in improving generalizability and power but is always…
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This study introduces a Bayesian multidimensional hierarchical item response theory (MHIRT) model to improve patient-reported outcome (PRO) assessments in total knee arthroplasty (TKA). Traditional unidimensional scoring fails to capture the multifaceted nature of recovery….
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US health systems receive up to 200 M monthly website visitors. Connecting patient searches to the appropriate workflow requires accurate classification. A dataset of searches on ~15 US health system websites was annotated, characterized, and…
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There are no prospective clinical studies evaluating artificial intelligence implementation for glaucoma detection in real-world settings. We developed an automated retinal photography and AI-based screening system and prospectively assessed its accuracy, feasibility, and acceptability…
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We reviewed 1016 FDA authorizations of AI/ML-enabled medical devices to develop a taxonomy capturing key variations in clinical and AI-related features. Quantitative image analysis remains the most common application, but its relative proportion has…
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Glaucoma is a globally prevalent disease that leads irreversible blindness. The visual field (VF) examination is important but time-consuming for visual function evaluation with high requirement of cooperation and reliability of patients. While color…
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Early outbreak detection, allowing rapid intervention, is essential to reduce the burden of healthcare-associated pathogen transmission, including multidrug-resistant bacteria. Digital, routine data-driven solutions are promising, but often proprietary, non-interoperable, or limited in functional scope….
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Drug-induced liver injury poses significant challenges in drug development and in clinical care. This study builds on prior work developing a Human Liver Virtual Twin by creating a Multiscale Computational Fluid Dynamics framework that…
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