人工智能代理人和呼吸道传染病的流行情报:朝着一个概念框架整合决策支持
Liuyang Yang1,2,3, Liyu Shan1, Xiaolin Cao4
1The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, Yunnan, China.
Journal of medical Internet research
|March 11, 2026
概括
本研究介绍了一种人工智能驱动的框架,以增强流行病情报,超越传统方法. 人工智能 (AI) 代理人充当数字流行病学家,以更快,更准确地检测和应对疾病爆发.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 人工智能的人工智能
背景情况:
- 传统的流行病情报是资源密集的,缓慢的,容易出现人为错误.
- 当前的系统在快速的数据解释和及时的响应方面扎.
- 这些限制阻碍了有效的疾病监测和控制.
研究的目的:
- 提出一个扩展的流行病情报框架,包括人工智能代理.
- 加强在疾病爆发中决策支持和干预优化.
- 创建一个持续适应和全球连接的流行病情报系统.
主要方法:
- 制定了一个四方框架,包括监控,风险评估,早期预警和人工智能驱动的决策支持.
- 利用多代理系统作为24 / 7数字流行病学家.
- 来自多源监控系统的综合异质信号,用于上下文风险评估和自适应预测.
主要成果:
- 人工智能代理可以充当数字流行病学家,改善响应时间.
- 该框架可提供量身定制的早期警告和可行的建议.
- 拟议的系统关闭了疾病检测和应对之间的循环.
结论:
- 人工智能代理人有潜力彻底改变流行病情报.
- 在现实世界中部署需要解决数据质量,互操作性和公平性方面的挑战.
- 透明度,包容性和弹性是成功将人工智能整合到公共卫生中的关键.
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