使用真实世界数据对基于人工智能的术前脆弱性指数进行外部验证
Chen Bai1, Feifei Xiao2, Mohammad Al-Ani3
1Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, United States.
概括
基于人工智能 (AI) 的脆弱指数准确预测了老年人手术风险. 这种人工智能工具使用电子健康记录 (EHR) 识别高风险患者,以获得更好的外科护理.
科学领域:
- 老年医学 老年医学
- 手术瘤学手术瘤学
- 医疗信息学 医疗信息学
背景情况:
- 术前脆弱性评估对于老年人手术风险分层至关重要.
- 传统的脆弱性测量通常是耗时和资源密集的.
- 这项研究通过使用电子健康记录 (EHR) 验证了基于人工智能 (AI) 的脆弱性指数.
研究的目的:
- 为外部验证基于人工智能的脆弱指数,用于手术前风险分层.
- 评估指数与术后结果的关联.
- 为了比较一般和特定服务的AI脆弱性指数.
主要方法:
- 之前开发的AI脆弱性指数的外部验证.
- 分析了1523,364名65岁以上的外科手术患者队列.
- 检查预测的脆弱性和30天死亡率,住院和出院处置之间的关联.
主要成果:
- 人工智能脆弱性指数显示,与不良的术后结果有很强的关联.
- 最脆弱的群体 (前20%),30天死亡率 (OR4.33) 和住院时间长 (2.53x) 的几率显著增加.
- 一般人工智能脆弱性指数的表现与服务特定指数相比或优于服务特定指数.
结论:
- 基于人工智能的手术前脆弱性指数有效预测了大型外部队列中手术后的结果.
- 该指数的效率和预测性能可以改善手术风险分层和患者的治疗结果.
- 人工智能驱动的脆弱性评估为改善老年人手术护理提供了一个有希望的方法.
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