流行病监测中的人工智能:革命性传染病监测监测
Abdallah Borham1, Lereen T Kamal1, Sungsoo Chun1
1Institute of Global Health and Human Ecology, School of Sciences and Engineering, The American University in Cairo, New Cairo, Egypt.
Frontiers in digital health
|December 22, 2025
概括
人工智能 (AI) 和机器学习 (ML) 可以通过分析数据来预防传染病,以便早期发现疫情和有效分配资源. 这项技术对于加强全球公共卫生安全至关重要.
科学领域:
- 公共卫生和流行病学
- 医疗保健中的人工智能
- 传染病监测 传染病监测 传染病
背景情况:
- 传染病影响全球超过一百万人,导致严重的死亡率和发病率.
- 人工智能 (AI) 越来越多地融入社区,使其在公共卫生领域的战略应用成为必要.
- 现有的疾病负担,以残疾调整寿命年 (DALYs) 衡量,突显了需要先进的预防策略.
研究的目的:
- 审查人工智能和公共卫生的交集,重点关注传染病预防.
- 探索机器学习 (ML) 和深度学习 (DL) 在疾病监测中的成功应用.
- 根据有关人工智能采用的当前文献提出公共卫生政策建议.
主要方法:
- 关于人工智能在传染病监测和公共卫生中的应用的最新文献的审查.
- 分析用于数据分析和实时监控的机器学习和深度学习算法.
- 考虑在公共卫生方面实施人工智能的技术接受和治理挑战.
主要成果:
- AI,ML和DL能够有效预测和监测传染病爆发.
- 这些技术促进了医疗资源的高效,以患者为中心的分配.
- 在传染病监测中成功使用了各种ML模型,以加强公共卫生安全.
结论:
- 人工智能为减轻全球传染病负担提供了巨大的潜力.
- 对人工智能的认真和熟练使用对于有效预防传染病至关重要.
- 解决技术接受和治理问题是最大限度地提高人工智能的公共卫生效益的关键.
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