规模化的实时临床分析:基于大型语言模型驱动的知识图表构建的平台
Shuang Cao1, Rui Li1, Rui Wu1
1Department of AI, Hill Research, Princeton, NJ 08540, United States.
生物医学研究人员现在可以使用ClinicalMind快速分析大型临床数据集,ClinicalMind是一个结合大型语言模型 (LLM) 和知识图的新平台,用于高效的临床分析.
科学领域:
- 生物医学信息学 生物医学信息学
- 临床数据分析
- 医疗保健中的人工智能
背景情况:
- 临床试验数据的指数增长压倒了传统的分析方法.
- 分析庞大的,非结构化的临床文件和电子医疗记录是研究人员面临的主要挑战.
研究的目的:
- 为实时临床分析开发一个可扩展的平台.
- 解决现有的以文档为中心和基于检索的方法的局限性.
主要方法:
- 大型语言模型 (LLM) 与知识图技术的整合.
- 实施两阶段图表更新策略和硬件加速.
- 实时分析超过11万份临床文件和6万份电子医疗记录.
主要成果:
- 实现了平均查询延迟1.7秒的高精度 (蓝色:0.85,红色:0.92).
- 实时处理和分析成千上万的临床文档.
- 显著超过现有的临床分析方法.
结论:
- 结合LLM和不断更新的知识图,可以实现可扩展的,低延迟的临床分析.
- 该平台支持实时临床决策和大规模证据综合.
- 提供了一个有效的解决方案,用于快速分析广泛的临床文档集合.
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