Department of Health Informatics and Data Science and Center for Health Outcome and Informatics Research’s
“An Introduction to Bayesian Modeling for Biomedical Research via COVID-19 Examples”
Abstract: This lecture will first introduce basic Bayesian modeling using COVID-19 data. Dr. Dong then will discuss a novel Bayesian approach that we recently published to estimate hospitalization risk for COVID-19 patients with comorbidities. The results indicate that cardiovascular diseases carry the highest hospitalization risk for COVID-19 adult patients, followed by diabetes, chronic respiratory disease, hypertension, and obesity.
Speaker: Qunfeng Dong, Ph.D.
Director, Center for Biomedical Informatics
Professor, Department of Medicine
Loyola Stritch School of Medicine
When: Wednesday, December 16, 2020 11:00 am – 12:00 pm
Join via Zoom Link: https://luc.zoom.us/j/81444737262
About the speaker: Dr. Dong’s research interests include analyzing high-throughput omics data, developing bioinformatics & biostatistical methods, and building integrative biological databases. Since March 2020, his research has mainly focused on COVID-19. More information is available at Center for Biomedical Informatics (CBMI).
Approval: This educational activity conforms to the guidelines required for an educational program to receive CME Category 1 credit. Your activity was approved for 1 category 1 credits towards the AMA Physician’s Recognition Award.
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