AIMI Grand Rounds
The AIMI Grand Rounds, sponsored by the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), is a new series launch held on every fourth Tuesday of the month that is a crucial initiative for disseminating the latest AI advancements in medicine, aiming to drive transformative innovations in healthcare. It provides healthcare professionals and learners with up-to-date, evidence-based, and transformative knowledge necessary for enhancing clinical decision making and healthcare delivery with AI. This series offers interdisciplinary lectures from renowned AI experts across medicine, engineering, and other fields, sharing cutting-edge research, clinical best practices, and other critical considerations related to AI implementation in healthcare. Participants will gain knowledge and tools to apply AI effectively in their practice, fostering innovation and excellence in patient care, and setting new standards in clinical excellence.
CME Credit Information
Each session is 1.0 credits: AMA PRA Category 1 Credits™ (1.00 hours); Non-Physician Participation Credit (1.00 hours). Credit can only be recorded via text during or up to 24 hours after the session. You must attend the live session to claim credit.
Grand Rounds Series
2026 Grand Rounds
2025 Grand Rounds
Upcoming Grand Rounds
Tuesday, September 22, 2026
8:00am-9:00am PT
RSVP for Webinar
Maame Yaa (Maya) Yiadom, MD, MPH, MSCI
Associate Professor of Emergency Medicine
Stanford University
Title: AI in the Loop: From Clinical Intelligence to Clinical Action
Dr. Maame Yaa (Maya) Yiadom is an Associate Professor of Emergency Medicine at Stanford University and a physician-scientist whose work focuses on precision emergency care, clinical artificial intelligence, and the integration of technology into real-world care delivery. Her research has advanced approaches to earlier recognition of time-sensitive conditions and the design of human-AI systems that support reliable execution of evidence-based clinical workflows. She leads a multidisciplinary research program focused on translating clinical evidence and AI-enabled decision support into measurable improvements in patient care.