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人工智能驱动的流行病控制:Deepseek在全球卫生弹性中的作用
Hong Jiang1,2, Meixian Wu1, Juan Yu3
1Zhuhai People's Hospital, The Affiliated Hospital of Beijing Institute of Technology, Zhuhai Clinical Medical College of Jinan University, Zhuhai, 519000, Guangdong, China.
Journal of translational medicine
|December 16, 2025
概括
人工智能平台DeepSeek使用先进的人工智能模型增强流行病管理,用于预警和趋势预测. 该系统旨在通过整合各种数据源来改善公共卫生响应来提高全球卫生弹性.
科学领域:
- 公共卫生信息学 公共卫生信息学
- 人工智能在医学中的应用
- 流行病学 流行病学
背景情况:
- 有效的流行病管理需要及时的数据分析和预测能力.
- 传统的监控系统在处理多样化的实时数据流时经常面临局限性.
- 人工智能的整合为提高公共卫生响应能力提供了潜在的解决方案.
研究的目的:
- 介绍DeepSeek,一个由人工智能驱动的平台,旨在彻底改变流行病管理.
- 概述平台在早期预警系统,趋势预测,治疗优化和公众咨询方面的能力.
- 突出人工智能在加强全球卫生弹性方面的潜力.
主要方法:
- 整合多个来源的实时数据,包括流行病学,社交媒体和移动数据.
- 应用深度学习模型,如长短期记忆 (LSTM) 和变压器.
- 利用可解释的决策框架来提高透明度和信任.
主要成果:
- 通过人工智能驱动的洞察力证明了公共卫生响应能力的提高.
- 促进早期预警系统,以积极介入流行病.
- 改进了趋势预测和治疗优化策略.
结论:
- 通过利用人工智能和大数据,DeepSeek提供了一种变革性的流行病管理方法.
- 解决数据隐私和模型准确性等挑战对于广泛采用至关重要.
- 该平台具有显著的潜力,可以加强全球卫生安全和弹性.
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