Student & Post-Doc Awards
Development of a Clinical Prediction Tool for Severe Outcomes in Pediatric COVID-19 Using Classical and Machine Learning Approaches
Participating Sites and Research Team
Yesmine Sahnoun
Dr. Sandra Isabel
British Columbia
BC Children’s Hospital (Vancouver)
Alberta
Alberta Children’s Hospital (Calgary)
Stollery Children’s Hospital (Edmonton)
Saskatchewan
Jim Pattison Children’s Hospital (Saskatoon)
Manitoba
The Children’s Hospital of Winnipeg (Winnipeg)
Ontario
Children's Hospital London Health Sciences Centre (London)
McMaster Children’s Hospital (Hamilton)
The Hospital for Sick Children (Toronto)
Children’s Hospital of Eastern Ontario (Ottawa)
Kingston Health Sciences Centre (Kingston)
Quebec
CHU Sainte-Justine (Montreal)
Montreal Children’s Hospital
CHU de Sherbrooke (Sherbrooke)
CHU de Quebec l‘Universite de Laval (Quebec City)
Nova Scotia
IWK Health Centre (Halifax)
Newfoundland
Janeway Children’s Health and Rehabilitation Centre (St. John’s)
What Do We Want To Know?
Our objective is to identify predictive factors associated with complications in patients diagnosed with COVID-19.
How Are We Doing It?
We plan to apply both traditional statistical methods and machine learning approaches to develop and evaluate predictive models.
How Is The Project Going?
Our ethics protocol was recently approved, and we are actively working on getting access to the dataset.
Who Can Participate?
No individuals can participate in this study, as it involves analysis of previously collected data only.
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