相关实验视频

Updated: Sep 15, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

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将机器学习与现实世界的数据结合起来,以识别临床实践指南中的差距:使用前性德国中风注册表和国家急性缺血性中风指南的可行性研究

Sandrine Müller1, Susanne Diekmann1, Markus Wenzel1,2

  • 1Fraunhofer Institute for Digital Medicine, Bremen, Germany.

JMIR medical informatics
|July 14, 2025
PubMed
概括

机器学习通过分析现实世界的数据,发现了德国中风血栓溶解指南中的差距. 患者的年龄影响了治疗决策,这表明急性缺血性中风护理的潜在指导方针改进.

关键词:
急性缺血性中风是急性缺血性中风.临床实践指南 临床实践指南准则的坚持 准则的坚持改善医疗保健 改善医疗保健机器学习是机器学习.现实世界的数据数据.

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