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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