Artificial Intelligence
EHR/Medical Informatics
Mark Mai, MD, MHS (he/him/his)
Assistant Professor
Department of Anesthesiology and Critical Care Medicine
Children's Healthcare of Atlanta
The Children's Hospital of Philadelphia
Decatur, Georgia, United States
Nymisha Chilukuri, MD (she/her/hers)
Clinical Assistant Professor, Division of General Pediatrics and Division of Clinical Informatics
Stanford University School of Medicine, United States
Advances in computing power and resources have facilitated a resurgence in predictive analytics, specifically in machine learning and artificial intelligence. Numerous models have been developed to address problems in pediatric healthcare, yet few have been implemented into practice and even fewer have been studied post-implementation. In this session, we will delve into several case studies that highlight both successful and challenging implementations of predictive analytics in pediatric healthcare. Our speakers will present up to three detailed examples, focusing on the barriers encountered and the strategies employed to overcome them. The session will conclude with breakout discussions, providing participants with the opportunity to engage, network, and share their own experiences and insights. These discussions aim to foster a collaborative environment where attendees can learn from each other and gain practical knowledge to apply in their own institutions.
SIG Speaker: Mark Mai, MD, MHS (he/him/his) – Children's Healthcare of Atlanta
SIG Speaker: Christopher Horvat, MD, MHA – UPMC/University of Pittsburgh
SIG Speaker: Alon Geva, MD, MPH – Boston Children's Hospital and Harvard Medical School
