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Updated: Sep 10, 2025

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胃肠病学和肝病学临床决策支持的大型语言模型

Isabella Catharina Wiest^1,2,3, Mamatha Bhat⁴, Jan Clusmann^1,3,5

¹Else Kroener Fresenius Center for Digital Health, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.

Nature reviews. Gastroenterology & hepatology

|August 22, 2025

概括

生成型人工智能 (AI),特别是大型语言模型 (LLM),为复杂的胃肠病和肝病提供先进的临床决策支持系统 (CDSS). 提供适应性,个性化的建议, 但面临偏见和互操作性等挑战.

科学领域:

胃肠病学
肝病学
人工智能
临床决策支持

背景情况:

胃肠病学和肝病学中的临床决策越来越复杂.
现有的临床决策支持系统 (CDSS) 由于性能和通用性问题而受到现实世界的限制.

研究的目的:

探索胃肠病学/肝病学领域日益复杂的临床复杂性和生成性人工智能的进展.
讨论大型语言模型 (LLM) 的潜力,以加强CDSS以改善临床实践.

主要方法:

在胃肠病学和肝病学中临床管理复杂性的演变.
对生成性人工智能的技术发展进行分析,特别是LLM和检索增强生成.
检查LLM在处理非结构化文本和集成信息以提供动态支持方面的能力.

主要成果:

通过处理各种数据并产生个性化的建议,LLM提供灵活,可适应的CDSS.
通过LLM增强的CDSS可以识别并发症并促进自然语言交互.
主要挑战包括人工智能偏见,幻觉,互操作性和医疗保健提供者培训.

结论:

生成性人工智能,特别是LLM,为开发更有效和更适应性的胃肠病学和肝病学提供了有希望的途径.
解决当前的挑战对于成功采用这些先进的人工智能驱动系统至关重要.

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