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肝病学中的生成人工智能:将多模式患者生成的数据转化为可操作的见解

Mason Lai¹, Irene Y Chen², Jennifer C Lai³

¹Department of Medicine, University of California, San Francisco, California, USA.

Hepatology communications

|July 14, 2025

概括

生成型人工智能 (GenAI) 和大型语言模型 (LLM) 可以整合家庭监测数据,用于复杂的肝硬化护理. 这使得能够主动管理诸如炎和肝脏脑病变 (HE) 等并发症.

科学领域:

肝病学肝病学是一种肝病学.
人工智能的人工智能
数字健康数字健康

背景情况:

肝硬化病的治疗是复杂的,具有高风险的失补偿,发病率和死亡率.
传统的情节性护理模式无法捕捉患者状态的动态变化.
在家监控提供连续的数据,但面临着整合的挑战.

研究的目的:

探索家庭监测技术用于肝硬化并发症的应用.
审查生成AI (GenAI) 和大型语言模型 (LLM) 在治疗肝硬化中的作用.
想象一下 GenAI 支持的家庭肝硬化护理.

主要方法:

审查新兴的家庭监控技术和可穿戴设备.
探索GenAI和LLM在处理多式联络患者数据方面的能力.
讨论如何将家庭数据与临床工作流程相结合.

主要成果:

基因AI和LLM可以获取,总结和分析多式联络患者数据.
这些技术促进了家庭和临床数据的整合.
基因人工智能可以支持临床决策和自主人工智能代理开发,用于患者选.

结论:

基因AI为复杂的肝硬化管理提供创新解决方案.
与GenAI集成的家庭监测可以改善对,肝脑病 (HE) 和虚弱的护理.
肝硬化护理的未来涉及GenAI支持的家庭监测和自主AI代理.

关键词:

人工智能的人工智能是人工智能.肝硬化是肝硬化的一种疾病.生成型的人工智能 (GAI)家庭监控家庭监控患者生成的数据是患者生成的数据.

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