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Lack of Data Access, but Not Availability, Hinders AI Training for High-Risk Conditions in Ontario
Fahreen Walimohamed1, Karim Keshavjee1
1Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Abstract:
Advanced disease prediction is an important step toward achieving a proactive healthcare system. New technologies such as artificial intelligence are very promising in their ability to predict the onset of future disease much earlier than has been possible in the past. However, artificial intelligence requires training and training requires data. In this study, we report on the ready availability, but lack of accessibility and real-time access to healthcare data required to treat five high-cost diseases that are predictable using AI and preventable using well-established evidence-based therapies. There is urgent need for action on the part of governments and other interest holders to define and invest in the infrastructure required to make data for training and deploying AI at scale more accessible.
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