题目：Representation Learning for Integrative Analysis of Multi-institutional EHR Data

主讲人：新加坡国立大学 周豆豆助理教授

主持人：统计学院 刘耀午教授

时间：2024年12月20日（周五）上午10:30-11:30

地点：西南财经大学光华校区光华楼1003会议室

报告摘要：

The widespread adoption of electronic health records (EHR) presents unprecedented opportunities for advancing biomedical research and improving patient care. However, integrating data across diverse healthcare systems is challenging due to differences in EHR coding systems, patient demographics, and care models. To overcome these challenges, this talk introduces novel methods for co-training multi-source feature embeddings using (1) block-wise overlapping noisy matrix completion and (2) graph neural networks. These methods address privacy concerns by relying on summary-level EHR data, enabling secure collaboration among institutions. The resulting harmonized embeddings support a range of clinical applications, including cross-institutional code mapping, feature selection, knowledge graph construction, and patient profiling, demonstrating their potential to enhance precision in healthcare decision-making.

主讲人简介：

Dr. Doudou Zhou is an assistant professor at the Department of Statistics and Data Science, National University of Singapore. Dr. Zhou obtained his Ph.D. degree in statistics from the University of California, Davis, and worked with Prof. Tianxi Cai as a postdoc at the Harvard T.H. Chan School of Public Health. His research interests include electronic health records, high-dimensional statistics, transfer learning, and federated learning.