医疗人工智能的创造性时代
L John Fahrner1, Emma Chen1, Eric Topol2
1Department of Biomedical Informatics, Harvard Medical School, Cambridge, MA, USA.
Cell
|July 11, 2025
概括
人工智能 (AI),包括大型语言模型 (LLM) 和多式人工智能,正在彻底改变医学. 这些技术提高了诊断,患者护理和预测,但临床整合仍面临挑战.
科学领域:
- 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 人工智能领域的快速发展,特别是LLM和多式人工智能,正在对医疗领域产生重大影响.
- 人工智能整合提供了改善诊断,患者互动和预测医疗保健的潜力.
研究的目的:
- 概述人工智能在医学中的变革潜力.
- 突出LLM和多式人工智能在临床应用中的能力.
- 确定阻碍在医疗保健中广泛采用人工智能的关键挑战.
主要方法:
- 对目前在诊断,患者互动和医疗预测方面的人工智能应用进行审查.
- 对医学报告和决策支持的自然语言处理的LLM能力的分析.
- 在整合多种数据类型 (例如成像,基因组学) 中对多式人工智能进行评估,以加强医疗查.
主要成果:
- 简单化医疗文档,帮助临床决策.
- 多模式人工智能通过整合多种数据在病理学和医疗查等领域表现出卓越的表现.
- 通过持续监测和预测, 人工智能驱动的工具可以提供主动的个性化医疗服务.
结论:
- 人工智能,尤其是LLM和多式人工智能,对医疗诊断,患者护理和预测有着巨大的前景.
- 应对数据偏差,隐私问题,监管框架和系统集成等挑战对于成功的临床实施至关重要.
- 医疗保健的未来与人工智能越来越紧密相连,
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