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Enhancing large language model clinical support information with machine learning risk and explainability: a feasibility study

Abstract Background Current machine learning (ML) prediction models offer limited guidance for individualized actionable management. Large language models (LLMs) can transform ML model-predicted risk estimates with Shapley Additive Explanations (SHAP) into clinically meaningful support information,...

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Principais autores: Yu-Chang Yeh, Hsin-Yu Yang, Ching-Tang Chiu, Anne Chao, Yu-Chen Chuang, Wing-Sum Chan
פורמט: Artigo
שפה:Inglês
יצא לאור: SpringerOpen 2026-04-01
סדרה:Intensive Care Medicine Experimental
נושאים:
Critical care
Machine learning
Large language model
Generative artificial intelligence
Clinical support system
גישה מקוונת:https://doi.org/10.1186/s40635-026-00900-w
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