Machine Learning Method for Measuring Blood Pressure and Monitoring Renal Perfusion Non-Invasively in the Neonatal Intensive Care Unit
Role
Chief Investigator
Description
This project firstly aims to develop machine learning algorithms capable of continuously monitoring blood pressure in babies born very preterm, using heart activity waveforms obtained from low-cost and non-invasive photoplethysmogram and electrocardiogram sensors. The second aim is the development of machine learning algorithms for early identification of acute kidney injury risk and early diagnosis when it does occur. It is expected that this work will provide non-invasive alternatives for measuring key neonatal health parameters, in turn leading to improved patient outcomes. This This work also has significant potential to support critical care in low-resource and remote areas.
Date
N/A
Project Type
GRANT
Keywords
N/A
Funding Body
Townsville Hospital and Health Service
Amount
29999
Project Team
N/A