In this episode of Moving Digital Health, MindSea CEO Reuben Hall talks with Dr. Raza Abidi, Professor of Computer Science and Professor of Medicine at Dalhousie University.
With decades of expertise working at the intersection of healthcare and knowledge management, Dr. Abidi has been applying his understanding of artificial intelligence (AI) and machine learning (ML) to healthcare projects for over 25 years.
Dr. Abidi locates the recent evolution of digital health within the necessity of making patient data available at the point of care. According to Dr. Abidi, the next step is to determine what can be done with the information we’ve amassed. He explains why other countries and regions may be ahead of North America on this front, addresses the remaining challenges that must be faced, and outlines the potential payoff for tackling these challenges.
Dr. Abidi shares some exciting AI-related projects currently in progress at Dalhousie University, including how data-based ML can provide decision support around both predictive modeling and patient stratification for risk assessment. Other applications range from early detection of disease to prevention of precious resource waste, from individual patient care to population-wide health projects.
Despite AI’s vast potential to improve healthcare, many of its tools—at least in their current states—are not inherently appealing to physicians. Dr. Abidi and Reuben dig into the challenges of working with black box models and discuss how explainable AI could improve physician trust. Dr. Abidi proposes a few additional uses of such devices, and shares some of the developments he’s most eagerly anticipating in the near future. Despite Dr. Abidi’s vast expertise in AI, machine learning, and health informatics, he presents these complex topics in an engaging and accessible way that leaves listeners better informed about the current and future state of digital healthcare. We thank Dr. Abidi for joining us to share his experience and insight, and we hope you’ll enjoy this conversation as much as we did.