【摘要】 罕见事件在各学科领域广泛存在，例如疫苗和药品的罕见不良反应、临床罕见疾病以及发生概率很小的临床结局等。这类事件的研究之所以受到广泛关注，是因为其发生通常会带来难以估量的严重后果。在大数据场景下，已涌现出包括基于抽样、类别加权、集成学习以及深度学习的众多罕见事件分析方法。本文系统总结了当前罕见事件分析方法的研究进展，介绍其基本原理以及适用场景，通过分析现有方法的优缺点，梳理归纳罕见事件研究的挑战，探索相关领域潜在的研究方向，为研究者提供参考。更多还原

【Abstract】 Rare events are widely prevalent in various disciplines, including rare adverse reactions to vaccines and drugs, clinical rare diseases, and low-probability clinical outcomes. The reason for research interest on such events is that their occurrence often brings incalculable and serious consequences. In the context of big data, numerous methods have emerged for rare event data analysis, including sampling based, category weighting, ensemble learning, and deep learning. This article systematically summarizes the research progress of current rare event data analysis methods, and introduces their basic principles and applicable scenarios. By analyzing the advantages and disadvantages of existing methods, the challenges of rare event research are sorted out and summarized, and potential research directions in related fields are explored to provide references for researchers.更多还原