Risk Estimation of Deterioration for patients in the cardiac ICU

The Artificial Intelligence (AI) initiative at SickKids, supporting the future of individualized paediatric care at SickKids and beyond. We are developing a unique paediatric methodology for the integration of AI and data science into clinical care. Critically ill children in pediatric and cardiac intensive care units are at a significant risk of clinical deterioration, which can lead to devastating outcomes, including death, long-term disability, and substantial healthcare costs. Current interventions often fail to provide timely and targeted care, as the early identification of at-risk patients remains a persistent challenge due to the complexity of high-resolution physiological data and the frequent occurrence of missing data in clinical monitoring systems. This internship is the first step to the development of an advanced tool that can estimate the risk of clinical deterioration in real time, enabling healthcare providers to deliver proactive and personalized care.

Faculty Supervisor:

Arvind Gupta;Karthik Kuber

Student:

Partner:

The Hospital for Sick Children

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Public administration

University:

University of Toronto

Program: