Existing prognostic models are useful for estimating the prognosis of lung adenocarcinoma patients, but there remains room for improvement. In the current study, we developed a deep learning model based on histopathological images to…
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Rare diseases, affecting ~350 million people worldwide, pose significant challenges in clinical diagnosis due to the lack of experienced physicians and the complexity of differentiating between numerous rare diseases. To address these challenges, we…
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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 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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The U.S. stock market, especially the tech-heavy NASDAQ, was deeply (no pun intended) rattled by a Chinese AI upstart called DeepSeek on Monday. It appears to have accomplished much of what large language models…
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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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What Is Retrieval-Augmented Generation?
With RAG, an LLM is better positioned to optimize its output before generating a response, says Tehsin Syed, Amazon Web Services’ general manager of health AI. This is valuable when a…
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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Predictive model performance may deteriorate when applied to data sources that were not used for training, thus, external validation is a key step in successful model deployment. As access to patient-level external data sources…
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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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