麦凯童,刘星彤,林晓妍,刘诗音,赵辰恺,杜江波.机器学习在流行病学中的应用进展[J].中华流行病学杂志,2024,45(9):1321-1326 |
机器学习在流行病学中的应用进展 |
Progress in application of machine learning in epidemiology |
收稿日期:2024-03-22 出版日期:2024-09-14 |
DOI:10.3760/cma.j.cn112338-20240322-00148 |
中文关键词: 机器学习 流行病学 人工智能 疾病诊断 风险预测 |
英文关键词: Machine learning Epidemiology Artificial intelligence Disease diagnosis Risk prediction |
基金项目:国家重点研发计划(2021YFC2700705);大学生创新创业训练计划(202310312014Z) |
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中文摘要: |
健康相关的人群数据收集和分析是流行病学研究的重要方面。近年来,随着大数据、互联网和云计算等领域的快速发展,人工智能逐渐进入流行病学研究者视野。越来越多的研究者尝试将人工智能算法应用于基因组测序和医学影像数据挖掘。人工智能在疾病诊断、风险预测等领域的应用范围迅速扩大。近年来,机器学习作为人工智能的一个分支,在流行病学研究领域的应用较为广泛。本文通过文献检索,针对机器学习在流行病学中应用的重点领域和前沿进展进行总结归纳,回顾机器学习发展的历史脉络,分析其在当下流行病学研究领域的经典案例和主要挑战,了解机器学习和人工智能算法目前的应用场景和未来的发展趋势,进而更好地发掘我国海量医学健康数据的流行病学研究价值。 |
英文摘要: |
Population based health data collection and analysis are important in epidemiological research. In recent years, with the rapid development of big data, Internet and cloud computing, artificial intelligence has gradually attracted attention of epidemiological researchers. More and more researchers are trying to use artificial intelligence algorithms for genome sequencing and medical image data mining, and for disease diagnosis, risk prediction and others. In recent years, machine learning, a branch of artificial intelligence, has been widely used in epidemiological research. This paper summarizes the key fields and progress in the application of machine learning in epidemiology, reviews the development history of machine learning, analyzes the classic cases and current challenges in its application in epidemiological research, and introduces the current application scenarios and future development trends of machine learning and artificial intelligence algorithms for the better exploration of the epidemiological research value of massive medical health data in China. |
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