Biostatistics Weekly Seminar

Cancer prognosis analysis via integrating molecular and histopathological imaging features

Shuangge “Steven” Ma, PhD
Department Chair and Professor
Department of Biostatistics and Bioinformatics Shared Resource
Yale Institute for Global Health

Modeling cancer prognosis is a “classic” yet still challenging problem. In the past two decades, high-throughput molecular data have been extensively used in such analysis. Very recently, it has been shown that histopathological imaging features, which are generated in the biopsy process, are also informative for modeling prognosis (and other outcomes/phenotypes). Molecular and imaging data contain overlapping as well as independent information. In our recent studies, we have developed regularization techniques, testing the degree of independent information for prognosis and integrating the two distinct types of data for prognosis modeling under homogeneity as well as heterogeneity.

Virtual: Zoom Link to Follow
06 September 2023

Speaker Itinerary

Topic revision: r2 - 31 Aug 2023, CierraStreeter

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