Presented by Lu Tang, PhD, Assistant Professor and Vice Chair for Education, Department of Biostatistics, University of Pittsburgh This paper introduces a new objective function and federated learning (FL) algorithm for deriving individualized decision rules (IDRs) that are robust to distributional uncertainty in heterogeneous data sources. It is motivated by the need to uniformly improve […]

Presented by Chao Huang, PhD, Assistant Professor, Department of Biomedical Sciences, Florida State University Alterations in subcortical brain structures, such as changes in the shape of the hippocampus, are typically interconnected and associated with the natural process of brain aging. Detecting and comprehending the geometric distinctions within these diverse subcortical brain structures is crucial for […]

Presented by: Ben Lengerich, Postdoc and Alana Fellow, MIT Comp Sci and AI Lab & the Broad Institute In biomedical data analysis, an emerging trend focuses on contextualizing observations within biological and real-world processes. This approach facilitates high-resolution, context-specific insights by integrating information across datasets, moving beyond analyzing datasets in isolation. However, modern AI systems […]

PHS Biostatistics and Bioinformatics Seminar presented by Dr. Yukinori Okada, MD, PhD, Professor, Department of Genome Informatics, The University of Tokyo Statistical genetics is a research field that evaluates causality of human genetic variations on diseases, using statistical and bioinformatics approaches. Recent developments of sequencing technologies have provided human disease genome data of hundreds of […]