多变点检测方法及其在精准医疗中的应用

Multiple change point detection methods and their applications in precision medicine

报告时间:11月7日 星期五9:30-10:50报告地点:管理科研楼一楼第二教室

Speaker: 李亚光

Abstract: Subgroup identification is a significant research area in statistics and machine learning, aiming to partition a heterogeneous population into more homogeneous subgroups to enable precise inference and personalized decision-making. Among the various tools available, changepoint analysis has emerged as a powerful approach for detecting structural changes in data sequences, and it plays an increasingly important role insubgroup identification.In this talk, we provide a systematic review of recent advances in subgroup identification methods based on efficientmultiple change point detection methods. We first introduce the two-stepmultiple change point detection method (TSMCD), and its application fromlinear regression to survival analysis, We then discuss the construction of the threshold variable, including the recent developments in the changeplane regression model and the change surface regression mode. This talkaims to provide researchers with a comprehensive perspective to promotethe further application and development of change point analysis in sub.group identification and precision medicine

Bio: 李亚光，中国科学技术大学管理学院特任副研究员，研究方向为复杂数据变点检测和个性化医疗。研究成果发表于《Journal of the Royal Statistical Soci-ety: Series B》《Biometrics》《Statistics in Medicine》

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