Machine Learning Advances in Predictive Pediatrics
A new tool anticipates health changes in hospitalized children.
Written by Philip Baker. 5-minute read
- Data Analytics
- Science in Practice
- Technology and Innovation
- A key objective in healthcare today centers around building tools that use electronic health records data to direct the course of treatment and improve patient outcomes.
- While tools exist to alert hospital caregivers to the potential decline of a patient’s condition, no effective tool has yet been widely implemented in pediatrics.
- Through their capstone project, two Master of Science in Biomedical Informatics students made advances in the field by using data from the University of Chicago’s Comer’s Children Hospital.
As healthcare professionals turn to clinical data to improve patient care, informaticians are utilizing advanced machine learning methods to predict risks in ICU transfers.