This retrospective study evaluated the efficacy of large language models (LLMs) in improving the accuracy of Chinese ultrasound reports. Data from three hospitals (January-April 2024) including 400 reports with 243 errors across six categories…
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Accurately predicting binding affinities between drugs and targets is crucial for drug discovery but remains challenging due to the complexity of modeling interactions between small drug and large targets. This study proposes DMFF-DTA, a…
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The UK healthcare sector is at risk of falling behind other European countries in adopting AI, according to a pan-European study.
The report, produced by healthcare AI research and development company Corti and YouGov, shows…
The Hong Kong University of Science and Technology has announced that its engineers have created what could be the world’s smallest multifunctional surgical robot. Made of hollow skeleton, optical fibre array, functionalized skin, and coated…
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Current State of Healthcare AI Implementation
While artificial intelligence has become increasingly prevalent in U.S. healthcare systems, with approximately two-thirds of hospitals utilizing AI-assisted predictive models, a striking disparity exists in their evaluation practices. According…
Chatbot-based multimodal AI holds promise for collecting medical histories and diagnosing ophthalmic diseases using textual and imaging data. This study developed and evaluated the ChatGPT-powered Intelligent Ophthalmic Multimodal Interactive Diagnostic System (IOMIDS) to enable…
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Urinary tract infections (UTIs) often prompt empiric outpatient antibiotic prescriptions, risking mismatches. This study evaluates the impact of “UTI Smart-Set” (UTIS), an AI-driven decision-support tool, on prescribing patterns and mismatches in a large outpatient…
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In this study, we present MedS-Bench, a comprehensive benchmark to evaluate large language models (LLMs) in clinical contexts, MedS-Bench, spanning 11 high-level clinical tasks. We evaluate nine leading LLMs, e.g., MEDITRON, Llama 3, Mistral,…
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Noninvasive methods for intracranial pressure (ICP) monitoring have emerged, but none has successfully replaced invasive techniques. This observational study developed and tested a machine learning (ML) model to estimate ICP using waveforms from a…
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Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis…
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