Prediction of the Microbial Origin of Presumed Sepsis in PICU Encounters
Team: Team Pandas
Program: Biomedical Engineering
We aim to use machine learning to accurately predict the microbiological origin of infection in children faster than the time it takes hospital lab tests to return. We hypothesize that we can develop predictive models analyzing a patient’s Physiological Time Series Data and electronic medical records to identify the origin of infection in the first 48 hours of PICU admission.
Our project photo picture is a magnifying glass identifying microorganisms. The magnifying glass is a metaphor for our highly sophisticated computational algorithm that our team has created.