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Updated: Jun 15, 2025

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Remote Laboratory Management: Respiratory Virus Diagnostics
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基于人工智能的流行病和流行病早期预警系统:系统范围审查
Christo El Morr1, Deniz Ozdemir2, Yasmeen Asdaah1
1School of Health Policy and Management, York University, Toronto, ON, Canada.
Health informatics journal
|August 22, 2024
概括
人工智能 (AI) 增强了流行病早期预警系统 (EWS),以更快地检测疾病. 解决数据质量,偏见和透明度对于可靠的人工智能驱动的公共卫生监测至关重要.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 计算机科学 计算机科学
背景情况:
- 及时发现疾病爆发对于有效的公共卫生反应至关重要.
- 人工智能 (AI) 提供了识别流行病和大流行病的模式的潜力.
- 预警系统 (EWS) 对于监测和应对公共卫生威胁至关重要.
研究的目的:
- 评估AI在流行病和流行病早期预警系统中的有效性.
- 确定挑战,并提出改进基于AI的EWS的策略.
- 评估人工智能系统在公共卫生监测中的预测能力.
主要方法:
- 采用了一种系统的范围审查方法.
- 包括在过去五年内发表的研究,重点关注EWS中的AI/机器学习.
- 在选1087.8之后,对33篇选定的文章进行了主题分析.
主要成果:
- 基于AI的EWS已经在各种应用程序和算法中证明了其有效性.
- 确定的挑战包括数据质量,模型可解释性,偏差和数据特征 (体积,速度,种类,可用性,颗粒度).
- 研究了减轻人工智能偏差和提高系统适应性的策略.
结论:
- 人工智能在提高流行病检测速度和准确性方面显示出显著的希望.
- 解决数据质量,偏差和模型透明度对于提高AI-EWS的可靠性和通用性至关重要.
- 未来的发展需要不断监测,改进和整合社会环境数据.
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