从世界卫生组织的疾病爆发新闻中提取的流行病学知识图表
Sergio Consoli1, Pietro Coletti2,3, Peter V Markov2,4
1European Commission, Joint Research Centre (JRC), Ispra, Italy. sergio.consoli@ec.europa.eu.
Scientific data
|June 10, 2025
概括
这项研究使用生成性人工智能和多个大型语言模型 (LLM) 来从世卫组织疾病爆发新闻中提取流行病学数据,创建用于增强疾病监测和公共卫生研究的知识图.
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:
- 人工智能 (AI) 和随时可用的新闻/社交媒体数据的融合为流行病监测提供了新的机会.
- 世界卫生组织 (WHO) 疾病爆发新闻 (DONs) 提供了关于全球疾病爆发的关键信息.
研究的目的:
- 利用生成性人工智能和大型语言模型 (LLM) 来从WHO DON中提取流行病学见解.
- 开发一个结构化知识图 (eKG) 来对公共卫生领域的知识进行细微表示.
主要方法:
- 一种使用多个LLM处理和提取WHO DONs的流行病学信息的整体方法.
- 构建流行病学知识图 (eKG) 来组织提取的数据.
主要成果:
- 一个来自WHO DONs的新型数据集,在 eKG.中结构化.
- 为访问和使用 eKG 数据开发服务和工具.
结论:
- 开发的eKG和相关工具为流行病学研究和疾病爆发分析提供了创新的资源.
- 这种方法提高了实时监控和应对公共卫生紧急情况的潜力.
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