Wednesday, October 3, 2018: 1:30 PM-3:15 PM
Room: S 214-216
At the conclusion of this session, participants will be able to:
- review the data on how the electronic medical record can be used to generate models that predict risk of healthcare-associated infections.
- apply machine learning approaches to stratify patients who present with clinical manifestations of sepsis.
- discuss the impact data-driven approaches can have in the management of patients in the intensive care unit.
Academicians, Clinicians, Epidemiologists, Fellows, Hospital epidemiologists, Infection preventionists, Infectious diseases pediatricians, Infectious diseases physicians, Investigators, Lab personnel, Medical students and residents, Members-in-training, Microbiologists, Pharmacists, Researchers, Scientists
Pediatric ID, Trainee, Epidemiology and Infection Control, Investigative ID, Adult ID
Vincent B. Young, MD, PhD, FIDSA, University of Michigan
Erica Shenoy, MD, PhD, Massachusetts General Hospital
Maximum of 1.75 hours of AMA PRA Category 1 Credit™
ACPE 1.75 knowledge-based contact hours of pharmacy CE
V. B. Young,