SAEMF/RAMS Resident Research Grant - $5,000

"NextGen Artificial Intelligence for Predicting Organ Support Needs From the Emergency Department"

Access to critical care resources and expertise in the United States is inequitable and the transfer of critically ill patients from outside hospitals to those with higher level of care is resource intensive. Improving triage assessment and risk stratification of critically ill patients presenting to the emergency department offers an opportunity for early identification of patients that would benefit from higher level of care, with the goal of improving patient outcomes and hospital resource allocation.

Recipient(s)

  • Samuel Chiacchia, MD

    Samuel Chiacchia, MD

    Stanford University

    "NextGen Artificial Intelligence for Predicting Organ Support Needs From the Emergency Department"

    Samuel Chiacchia, MD, is a postgraduate year two (PGY2) in the Stanford Emergency Medicine Residency Program. He grew up in Colorado Springs, Colorado and is a graduate of Princeton University and the Icahn School of Medicine at Mount Sinai. Dr. Chiacchia’s research interests are at the intersection of emergency medicine, critical care, and informatics, where he hopes to develop clinical decision support tools that improve risk stratification among critical and peri-critical patients in the emergency department. He plans to pursue a fellowship in critical care and practice academic emergency and critical care medicine while pursuing a career in grant funded research as a physician scientist. He is grateful for the generosity of the Society for Academic Emergency Medicine Foundation (SAEMF), whose support through the SAEMF/RAMS Resident Research Grant will work to advance his career aspirations in science and medicine.