BIHE Monthly Seminar – Integration of AI and its impact on health disparities in Medical Education
BIHE Monthly Seminar
March 19, 2025
12:00 PM - 1:00 PM
Join us for an engaging seminar on the integration of AI in medical education, with a special focus on health disparities and ethical considerations. This seminar will explore how UIC-COM integrates education about AI into the curriculum, while addressing health disparities to ensure the responsible, and transparent use of AI in clinical decision-making.
Date posted
Mar 5, 2025
Date updated
Mar 5, 2025
Speakers
Dr. LInda Chang | Associate Professor of Clinical Family Medicine | Family and Community Medicine - Rockford
Dr. Linda Chang is an educator and curriculum developer specializing in pharmacology, ebm, and AI integration in healthcare. With a strong focus on interprofessional education, her work spans medical education, population health, and chronic disease management. She has co-led initiatives to integrate AI into medical training, develop quality improvement curricula for residents, and advance research on social determinants of health. Through collaborative efforts across disciplines, Dr. Chang continues to pioneer innovative programs that equip future healthcare professionals with essential skills to address health disparities and improve patient outcomes.
Dr. Radhika Sreedhar | Associate Professor of Clinical Medicine, Director of Curricular Integration | Academic Internal Medicine
An internal medicine physician and health professions educator, Dr. Sreedhar leads the Evidence Based Medicine subtheme in the College of Medicine, co-directs the Body Systems and Homeostasis block, serves as the Director of Curricular Integration, Assistant Clerkship and Sub-internship Director for Internal Medicine. She has been instrumental in pioneering initiatives to weave artificial intelligence into the medical curriculum, co-led the effort to create an AI elective and helped establish an Artificial Intelligence in Medicine track. Her research spans a broad spectrum of interests, including the assessment of medical students' proficiency in providing discharge instructions, using simulation for evaluating interprofessional teams, enhancing students' ability to appraise medical literature through simulation activities, and exploring the potential of large language models in delivering narrative feedback.