About the Project
The traditional hospital-focused model of care neglects monitoring and treating diseases at home. A number of intelligent monitoring systems exist for clinical abnormalities prediction for patients who are confined to hospital beds, but few attempts have been made to develop such a predictive system for home care that could prevent and minimize health-related risk at an early stage. As a result, recovering patients who leave the hospital after treatments are known to have adverse outcomes due to lack of efficient alert systems. In particular, children at risk of serious infection and sepsis are often discharged home with ‘safety-netting’ advice for parents and carers to subjectively observe signs of deterioration.
This project, in collaboration with Queensland Health, aims to develop a probabilistic cloud-based health monitoring and risk prediction system that can predict clinical abnormalities based on streaming data of vitals of children with possible serious infection at home.
About the Team
The project commenced in April 2023 with the recruitment of PhD researcher Hrishi Patel, who is based at The University of Queensland. Hrishi is supervised by Dr Sen Wang, Dr Adam Irwin (Queensland Health), and Professor Shazia Sadiq. This project is a close collaboration with leading experts in Queensland Health on investigating machine learning techniques for designing risk predictive models in outpatient settings, to mitigate the risk of sepsis in children.
This project is one of three CIRES projects with Queensland Health related to paediatric sepsis management and more details of the other two projects can be found via the links below:
Expanding Data Sets to Allow Improved Critical Care for Children – Inpatient Risk Prediction
Improving Sepsis Management through Better Data and Rapid Learning
Dr Sen Wang (Principal Advisor)
Dr Adam Irwin (Queensland Health)
Mr Hrishi Patel (PhD Researcher)