| 吴璇,张艳秋,孙定勇.机器学习在结核病监测预警和干预策略效果评价上的应用[J].中华流行病学杂志,2025,46(8):1495-1501 |
| 机器学习在结核病监测预警和干预策略效果评价上的应用 |
| The application of machine learning in tuberculosis surveillance, early warning, and evaluation of intervention strategies |
| 收稿日期:2024-12-09 出版日期:2025-08-21 |
| DOI：10.3760/cma.j.cn112338-20241209-00782 |
| 中文关键词: 机器学习 结核病 流行病学 |
| 英文关键词: Machine learning Tuberculosis Epidemiology |
| 基金项目:河南省科技发展计划（242102311109）；河南省医学科技攻关计划联合共建项目（LHGJ20210136） |
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| 中文摘要: |
| 结核病作为全球主要的公共卫生挑战之一，其流行病学研究对于控制和预防至关重要。随着大数据时代的到来，机器学习相较于传统方法在处理复杂、高维度数据集和提供精准预测结果方面呈现优势。本文介绍了机器学习在结核病病例发现与诊断、风险因素分析、预测建模、评估干预策略等方面的应用，为更加深入地挖掘结核病流行病学研究价值提供了新手段。 |
| 英文摘要: |
| As one of the major public health challenges globally, tuberculosis requires epidemiological research for its control and prevention. With the advent of the big data era, machine learning has advantages over traditional methods in handling complex, high-dimensional datasets and providing accurate predictive results. This paper introduces the application of machine learning in the discovery and diagnosis of tuberculosis cases, risk factor analysis, predictive modeling, and evaluation of intervention strategies, providing new means for more in-depth exploration of the value in tuberculosis epidemiological research. |
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