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Identifying the impact of social determinants of health on the incidence and outcomes associated with acute kidney injury using a machine learning approach
Acute kidney injury (AKI) is a syndrome which involves a sudden decrease in kidney function because of functional or structural impairment. It is a global issue and affects more than 7% of hospitalization in Canada. Unfortunately, although there has been improvement in the recognition and management of AKI, it continues to be a disease associated with poor outcomes. Furthermore, we know that the social determinants of health have a significant impact on outcomes; however, there is very limited information available in AKI. This project will utilize machine learning to identify high risk populations with AKI and determine the intersection with the social determinants of health. The partner organization will have the opportunity to generate important information to help guide future health policy decisions for patients with AKI.
Faculty Supervisor:
Dean Eurich
Student:
Partner:
OKAKI
Discipline:
Life Sciences
Sector:
Health and Related Sciences & Technology; Information and cultural industries; Professional, scientific and technical services
University:
University of Alberta
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.