About this Event
Artificial intelligence (AI) is rapidly permeating nearly every sector of society, including healthcare, yet its inherent complexity makes interpreting AI-generated output challenging. In high-stakes contexts like medical decision-making, misinterpretations of AI output can compromise patient safety. Data visualization offers a powerful pathway for making complex information more comprehensible, especially for individuals with low literacy and numeracy skills. This talk asks: Can we harness data visualization to make AI-generated output more meaningful, interpretable, and trustworthy in healthcare? I will present (1) current challenges and limitations of AI output in clinical contexts, (2) evidence from prior work demonstrating how visualization improves patient comprehension, and (3) my team’s early exploratory efforts to develop patient-facing visualizations of AI-generated output.
Meghan Reading Turchioe, PhD, MPH, RN, FAHA, is an Assistant Professor of Nursing at Columbia University Irving Medical Center and a nurse scientist whose work sits at the intersection of artificial intelligence, data visualization, and health equity. Her research focuses on developing human-centered strategies to help patients and clinicians interpret complex health information, with particular expertise in atrial fibrillation management and shared decision-making. Dr. Turchioe leads interdisciplinary projects that use data visualization to make AI-generated output more comprehensible, meaningful, and actionable for diverse audiences. As Chair of the AMIA Nursing Informatics Policy Committee and a nationally recognized voice in digital health innovation, she is committed to shaping more just and equitable digital futures in healthcare.
Event Venue & Nearby Stays
Russell Hall 4th Fl - Smith Learning Theater, 525 West 120th Street, New York, United States
USD 0.00
