Jordan Engbers, Chief Science Officer of Cohesic, a data scientist who spent years in clinical research, is painfully aware of the chasm between the promise and reality of AI in healthcare. While an AI model might work within a study where researchers systematically gather, clean up, and standardize the data, real-world healthcare data is often too messy and unreliable to use for clinical decisions.

Dr. Karen Cross, a plastic and reconstructive surgeon and CEO of MIMOSA Diagnostics, saw countless patients with diabetes and chronic wounds in her clinic. People with diabetes have an increased risk of developing pressure wounds due to complications like poor circulation and nerve damage. Many of her patients came into her clinic too late to prevent complications and ultimately had lower extremity amputations to prevent fatal infections.

Industry members in the INOVAIT Network are developing AI technologies that are revolutionizing the diagnosis and treatment of disease and improving patient outcomes while building the Canadian healthcare economy. The health data these companies need to create their technologies most often reside with Canadian healthcare institutions that are reluctant to share data with commercial partners due to caution stemming from a lack of clarity in privacy legislation and historical practices focused primarily on minimizing privacy and security risks.