Project Code
MRCPHS26Br Millard
Project Type
Dry lab
Research Theme
Population Health Science
Project Summary Download
Summary
There are multiple adverse events or health outcomes that can occur during pregnancy or shortly after birth such as emergency caesarean section, pre-term birth, and complications meaning that the newborn is admitted to the neonatal intensive care unit. Predicting these adverse events is essential for identifying those at high risk so that monitoring or more targeted care can be provided. This project aims to develop and evaluate statistical and machine learning models for predicting adverse events during pregnancy, in a way which is explainable to the clinicians and patients.
Lead Supervisor
Dr Louise Millard
Lead Supervisor Email
University Affiliation
Bristol