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Prediction of the Microbial Origin of Presumed Sepsis in PICU Encounters
Team: Team Pandas
- Program: Biomedical Engineering
- Course: Precision Care Medicine
- Year: 2022
Project Description:
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.
Project Photo:
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.
Project Mentors, Sponsors, and Partners
- Jim Fackler
- Jules Bergmann
- Luis Ahumada
- Casey Overby Taylor
- Joseph L Greenstein