人工智能在检测和预测医疗保健相关感染中的使用和性能:系统性审查
Chiara Barbati1, Luca Viviani2, Riccardo Vecchio3
1School of Public Health, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy; PhD National Programme in One Health approaches to infectious diseases and life science research, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy.
Artificial intelligence in medicine
|December 3, 2025
概括
人工智能 (AI) 模型在检测和预测医疗相关感染 (HAI) 中表现强. 虽然人工智能经常超过传统方法,但需要进一步的研究来标准化评估和评估现实世界的影响.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 传染病流行病学 传染病流行病学
背景情况:
- 数字化的医疗数据和人工智能的进步使得新的传染病管理策略成为可能.
- 医疗相关感染 (HAI) 构成了重大挑战,需要改进检测和预测方法.
研究的目的:
- 系统地审查和综合人工智能模型性能证据,用于HAI检测和预测.
- 评估人工智能在抗击HAI方面的技术和临床实用性.
主要方法:
- 从2018年7月到2024年2月,在主要数据库 (PubMed,Embase,Scopus,Web of Science) 进行了全面的文献搜索.
- 包括专注于人工智能的实验和观察研究,用于HAI检测和预测.
- 分析主要结果 (技术性能指标,如AUROC,回忆,精度) 和次要结果 (临床,组织,经济影响).
主要成果:
- 包括121项研究,其中25项专注于HAI检测,93项专注于HAI预测.
- 超过一半的HAI检测研究实现了AUROC>0.90;HAI预测研究显示了更可变的性能.
- 在81.3%的比较研究中,人工智能模型的表现优于传统方法.
结论:
- 人工智能模型的性能与HAI检测和预测的传统方法相提并论或优越.
- 绩效评估仍然存在挑战,包括缺乏比较研究,有限的前性研究,以及对组织影响的评估不足.
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