传染病监测早期预警系统中的人工智能:系统性审查
Ismael Villanueva-Miranda1, Guanghua Xiao1,2, Yang Xie1,2
1Department of Health Data Science and Biostatistics, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Frontiers in public health
|July 8, 2025
概括
人工智能 (AI) 可以通过提高疫情检测和预测来改善传染病早期预警系统 (EWS). 解决数据质量,透明度和道德问题对于实现人工智能在公共卫生监测中的全部潜力至关重要.
科学领域:
- 公共卫生 公共卫生
- 传染病流行病学 传染病流行病学
- 医疗保健中的人工智能
背景情况:
- 传染病是一个重大的全球卫生挑战,由全球化和气候变化加剧.
- 早期预警系统 (EWS) 对于及时的疾病监测和应对至关重要.
- 人工智能 (AI) 提供了先进的工具来增强EWS的能力.
研究的目的:
- 系统地审查人工智能在传染病中的当前应用.
- 确定这一领域的关键人工智能技术,数据源,好处和挑战.
主要方法:
- 使用Semantic Scholar (2018年以后) 按照PRISMA指南进行了系统的文献搜索.
- 选了600个记录,在删除重复和无关文章后,最终审查包括了67项相关研究.
主要成果:
- 机器学习 (ML),深度学习 (DL) 和自然语言处理 (NLP) 是EWS中普遍使用的AI技术.
- 综合了各种数据来源,包括流行病学,网络,气候和废水数据.
- 关键的好处包括更早的疫情检测和更好的预测准确性,而挑战涉及数据质量,偏见,模型透明度,整合和道德考虑.
结论:
- 人工智能对加强传染病EWS具有重大前景.
- 解决数据局限性,提高模型可解释性,确保道德实施,促进合作对于成功地将人工智能整合到公共卫生中至关重要.
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