人工智能精准医学的价值与成本:系统性审查和回归分析
Yue Zhang1, Ziwei Lin2, Yot Teerawattananon1,3
1Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
NPJ digital medicine
|December 24, 2025
概括
精准医学中的人工智能 (AI-PM) 显示出高的成本效益,经常节省资金或以负担得起的方式改善健康结果. 然而,价值异质性和采用不确定性仍然存在.
科学领域:
- 卫生经济学 卫生经济学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 精准医学 (PM) 正在被人工智能 (AI) 改变.
- 了解人工智能精准医学 (AI-PM) 的经济价值对于医疗保健的采用至关重要.
- 关于AI-PM成本效益的证据需要系统的综合.
研究的目的:
- 综合现有关于AI-PM的成本效益的证据.
- 评估价值与成本,并确定影响AI-PM经济影响的因素.
- 探索AI-PM采用和价值的不确定性.
主要方法:
- 在五个数据库中进行系统的文献搜索,以对AI-PM进行经济评估.
- 使用ECOBIAS检查清单进行数据提取和偏差风险评估.
- 用于异质性探索的成本效益分析和基于机器学习的回归的定量总结.
主要成果:
- 包括AI-PM的48个经济评估 (31个成本效益分析).
- 在89%的基准案例分析中,AI-PM节省了成本或具有成本效益.
- 观察到适度的健康益处与最小的额外成本,但发现了高价值的异质性.
结论:
- 人工智能-PM显示出显著的成本效益,尽管在评估中有可能产生系统的乐观情绪.
- 净货币收益的异质性与建模选择和系统级因素有关.
- 低适应性和报告不足的价值因素为AI-PM采用创造了不确定性.
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