David Chestek, DO
Associate Professor of Clinical Emergency Medicine
Department of Emergency Medicine
About
Dr. David Chestek is a practicing board-certified Emergency Medicine Physician and Clinical Informaticist. He completed his undergraduate degree in Biomedical Engineering because of an early love of technical science and health. He ultimately decided he wanted to work more closely with people and went to medical school. During his Emergency Medicine Residency, he found informatics to be the perfect outlet for his skill set. After completing a post-residency fellowship in Clinical Informatics at UIC, he joined the faculty in the Emergency Department. Currently, he balances his time between clinical practice in Emergency Medicine and his duties within clinical informatics as Chief Medical Information Officer at UI Health. He serves as a bridge between physicians and information services staff for operational projects. His current research projects include building custom large language models for healthcare. His interests include Artificial Intelligence, remote patient monitoring, data interoperability, data visualization, and hospital operations, among others.
Selected Grants
NIH, COVID19 Personalized Analytics Wearable Biosensor Platform for Early Detection of COVID-19 Decompensation (DECODE),, Co-I
NIH, A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults, Director of Remote Participant Monitoring Hub
ARPA-H, Dept of the Interior, Dept of the Interior, Creating AI-enabled all-health team data (CAIDF), Co-I
Publication Aggregators
Education
Fellowship, Clinical Informatics – University of Illinois Chicago (UIC)
Emergency Medicine Residency – Midwestern University, Chicago, IL
D.O. – Edward Via College of Osteopathic Medicine (VCOM), Virginia
B.S. – Biomedical Engineering, Case Western Reserve University
Research Currently in Progress
Dr. Chetek’s current scholarly work centers on the intersection of artificial intelligence and clinical practice, with a particular emphasis on developing and evaluating specialized large-language models for healthcare.