揭示大型语言模型在改变慢性疾病管理中的潜力:混合方法系统审查
Caixia Li1, Yina Zhao1, Yang Bai2
1The Department of Nursing, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Journal of medical Internet research
|April 16, 2025
概括
大型语言模型 (LLM) 通过提供准确的健康信息和支持,在治疗慢性疾病方面表现有前途. 然而,隐私,高级任务和个性化方面的挑战需要进一步开发用于临床使用.
科学领域:
- 医疗保健中的人工智能
- 数字健康数字健康
- 慢性疾病管理 慢性疾病管理
背景情况:
- 慢性疾病是一个重大的全球健康挑战,导致全球大多数死亡.
- 大型语言模型 (LLM) 为优化慢性疾病管理提供了潜力,但证据有限.
研究的目的:
- 审查在慢性疾病管理中使用LLMs的可行性,机遇和挑战.
- 综合从预防到长期护理的各个领域的证据.
主要方法:
- 按照PRISMA指南进行系统审查,搜索11个数据库.
- 包括对慢性疾病的LLM进行干预和模拟研究.
- 评估了方法质量,并进行了可行性元分析.
主要成果:
- 20项研究检查了LLMs的癌症,心血管和代谢障碍.
- 终身医疗证明了可行性,产生了准确的健康建议 (准确率为71%).
- 检索增强的LLM显示出比通用LLM更高的准确性.
结论:
- 在多个层面上,LLM显示出改变慢性疾病管理的潜力.
- 临床应用还在芽;需要关注数据安全,微调和与可穿戴设备的集成.
- 随着进一步的发展,LLM可以成为医疗保健专业人员的宝贵补充.
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