Supporting public health applications of artificial intelligence to improve health equity and prevent chronic diseases in the population
Description: Predictive risk algorithms for chronic disease are used by organizations like Public Health Ontario (PHO) for population health surveillance, examining the contribution of risk factors to disease, and assessing the impact of prevention strategies. Vast amounts of population health data are now available and able to support a wide range of "big data" approaches for chronic disease risk prediction. Population health has traditionally used simple risk prediction methods, however, artificial intelligence (AI) and machine learning (ML) are ideally suited to enhancing population risk prediction tools. To date, however, evidence on risk prediction using these methods for population health applications is limited and it is unclear how AI approaches could be used to benefit health protection, promotion, prevention and health equity. The objectives of the proposed program of work are to: 1) develop an AI strategy for PHO, the host organization; 2) develop two new risk prediction models for dementia and multiple chronic disease using AI methods; and 3) support public health units in building AI capacity. It is important for Canada to build capacity for AI, as there is significant potential for these methods to support population health surveillance and disease prevention.
Amount: CA$178,500
Funding type: fellowship
Funder scheme: Health System Impact Fellowships - Post-Doctoral in Equitable AI/PPH 2-year
Start date: 2019-09-01
End date: 2022-08-31
Investigator: Stacey Fisher
Institution: Public Health Ontario (Toronto)
Funded outputs count: 0
Funder award ID: 166363_1
OpenAlex ID: G669222220