Originally from Canada, Dr. Andrew Deonarine completed his MD at the University of Toronto and specialized in preventive medicine and public health at the University of British Columbia, and also completed a MHSc in Health Sciences, where he had the opportunity to pursue a thesis project Stanford University in biomedical ontologies . Through the Clinician Investigator MD/PhD Program, he completed a PhD in bioinformatics at the University of Cambridge, and completed his clinical informatics board certification at Harvard Medical School, where he studied as a Friedman Scholar. Dr. Deonarine has worked in public health units and in primary care informatics before starting at Mount Sinai Hospital in September, 2024. He currently works in the Department of Scientific Data and Computing as a Principal Physician Informaticist under the direction of Dean Patricia Kovatch.
Title of Talk: De Novo exposomic geospatial assembly of chronic disease regions with machine learning & network analysis
Determining spatial relationships between diseases and the exposome is limited by available methodologies. aPEER (algorithm for Projection of Exposome and Epidemiological Relationships) is a novel algorithm that uses machine learning (ML) and network analysis to find spatial relationships between diseases and the exposome in the United States. We were able to reidentify the Stroke and Diabetes Belts, regions with increased stroke and diabetes mortality, with high precision using ambient air pollution concentrations, highlighting the potential role of the exposome in the pathogenesis of these chronic diseases.
Time: Sept. 10, 2025 12:00 PM Eastern Time
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