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  • Rush Medical College, Chicago, IL - MD
  • Rush University Medical Center - Residency in Internal Medicine, Chief Resident
  • University of Maryland - Fellowship in Pulmonary and Critical Care
  • Rush Medical College, Chicago, IL - M.S. in Clinical Research

Professional Activities

Majid Afshar, MD, is a tenured Associate Professor in the Division of Allergy, Pulmonary and Critical Care Medicine where he co-leads the Critical Care Data Science Lab for the Department of Medicine. Dr. Afshar is also the Director of the Learning Health System in the Institute for Clinical and Translational Research in the School of Medicine. He has helped to build a program supported by both the university and health system to perform data-driven, bedside evaluation of interventions to improve healthcare delivery. Dr. Afshar is part of the UW Health informatics leadership team and has helped with the implementation and evaluation of emerging technologies in artificial intelligence. He helped guide one of the first real-time natural language processing pipelines in healthcare delivery for clinical decision support. In addition, he is part of the pioneering work to deploy generative AI technologies, including large language models, in health operations. He has hosted several national data challenges (National NLP Clinical Challenge and BioNLP Workshop) to advance the science in diagnostic decision support systems and was appointed as a chartered member of the NIH Digital Health and Clinical Informatics Study Section. He has co-chaired conferences with the American Medical Informatics Association and mentored multiple trainees in the lab to receive career development grants in Data Science.

Clinical Specialties

Dr. Afshar's clinical interests include the medical intensive care unit and taking care of patients with critical illness (i.e., sepsis, ARDS, alcohol-related liver disease).

Research Interests

View Dr. Majid Afshar’s publications on NCBI My Bibliography

As a physician-scientist, Dr. Afshar is at the forefront of advancing the prevention and early identification of diseases through artificial intelligence (AI), with a special focus on clinical translational natural language processing. His pioneering work involves leveraging predictive analytics and electronic health record data to enhance screening and diagnosis processes for critically ill patients. Under his leadership, his research lab has evolved into a comprehensive hub that encompasses the entire data science lifecycle, from the development of innovative models to their clinical implementation and health impact evaluation. As a principal investigator on several NIH grants, Dr. Afshar is actively involved in implementing and assessing AI models within the health system, focusing on their effectiveness as real-time clinical decision support tools. His extensive body of work, which includes over 100 peer-reviewed publications in both informatics and clinical journals, underscores his significant contributions to the field.
Dr. Afshar is acutely aware of the challenges posed by machine learning models, particularly the risk of perpetuating social and statistical biases, which remain significant concerns within AI applications in healthcare. This awareness informs his commitment to addressing health disparities, as evidenced by his recent studies on substance misuse algorithms. Leading with a team science approach, Dr. Afshar is dedicated to identifying and mitigating bias in data-driven tools deployed in hospital settings. He firmly believes in the transformative potential of AI in healthcare delivery but emphasizes the need for continued research to understand how to construct and utilize these models safely and effectively at scale.