Title: Cancer Human Disease Networks (cHDNs) via Deep Learning SEER-Medicare

Presented by Shuangge Ma, Professor, Yale School of Public Health

DATE:  Friday, December 5, 2025, 10:00 AM, AUST 247

Meeting Link: WebEx link

Coffee will be available at 9:30 AM in the Noether Lounge (AUST 326)

Abstract: Cancer patients often also suffer from other disease conditions. For more effective management and treatment, it is crucial to understand the “big picture”. Human disease network (HDN) analysis provides an effective way for describing the interrelationships among diseases. The goal of this study is to mine the SEER-Medicare data and construct the HDNs for major cancer types for the elderly. For network construction, we adopt penalized deep neural networks (pDNNs). The DNNs can be more flexible than the regression-based and other analyses, and penalization can effectively distinguish important disease interconnections from noises. As a “byproduct”, we establish the asymptotic properties of pDNNs. The constructed cHDNs are carefully analyzed in terms of node, module, and network properties.

Bio:  Dr. Shuangge (Steven) Ma is a Professor of Biostatistics at Yale School of Public Health. His research interests include genetic epidemiology, EHR data analysis, cancer biostatistics, and deep learning. He obtained his Ph.D. in Statistics from the University of Wisconsin, Madison in 2004. He was a Postdoctoral Fellow at the University of Washington, Seattle between 2004 and 2006 and has been at Yale University afterwards.