U of T launches Temerty Centre for AI Research and Education in Medicine

Our daily interactions with technology create vast amounts of data and analytics giving rise to what has been dubbed the “artificial intelligence revolution.” Now, a new research centre at the University of Toronto’s Temerty Faculty of Medicine aims to harness the incredible promise of AI in the realms of medicine and health care.

The Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM) launched this week at U of T, solidifying Toronto’s place at the nexus of AI, data science and the health sciences.

“Toronto is uniquely positioned to lead globally in artificial intelligence in healthcare,” says Professor Muhammad Mamdani, who was recently appointed the inaugural director of T-CAIREM for a five-year term. “Our expertise in medicine and allied health sciences, computer science, statistics, mathematics and engineering is among the best in the world.”

The goal of T-CAIREM is to create a forum that brings together this multidisciplinary expertise so members can share their experiences and collaborate through common interests – and a cutting-edge data and computing environment – that will transform health care in innovative and exciting ways.

Mamdani is well placed to bring together the worlds of AI and medicine. He is a professor in the Leslie Dan Faculty of Pharmacy, the department of medicine in the Temerty Faculty of Medicine and at the Institute of Health Policy, Management and Evaluation at the Dalla Lana School of Public Health. He’s also the vice-president of data science and advanced analytics at Unity Health Toronto, where his research team develops advanced analytics solutions and deploys them into clinical practice, to improve patient outcomes and hospital efficiency.

Based in U of T’s department of laboratory medicine and pathobiology, T-CAIREM’s work will focus on three pillars: research, education and data infrastructure. The centre brings together some of North America’s brightest researchers, including:

• Research co-leads Anna Goldenberg (computer science/SickKids) and Mjaye Mazwi (pediatrics/SickKids)

• Education lead Laura Rosella (Dalla Lana School of Public Health) and learner co-leads Vinyas Harish (MD/PhD student) and Felipe Morgado (MD/PhD student)

• Infrastructure co-leads Sean Hill (psychiatry/CAMH) and Alistair Johnson (computer science/SickKids).

To ensure T-CAIREM’s programs fulfill their education mandate, two students are crucial members of the centre’s leadership team. Morgado, an MD/PhD program learner, is one of them. “The world has adjusted to AI so quickly,” says Morgado. “And this rate of adoption will continue to increase as the tools and data become more available. Today’s students will need to know how to use these tools effectively if we’re going to use them to improve patient care.”

The T-CAIREM team is launching several initiatives this month for students in undergraduate, graduate and professional programs. The Trainee Rounds, aimed at graduate students across faculties as well as MD students, will give selected students the opportunity to showcase their work to leaders in the AI and health-care research communities. In addition, a Summer Research Studentship Program will pair undergraduate and medical students with a U of T faculty supervisor to explore AI in medicine.

There are also opportunities for experienced researchers. Two $200,000 Temerty Innovation Grants for AI in Medicine are available for up to two years for multidisciplinary teams working on projects with the potential to transform health care using AI over the coming decades.

T-CAIREM’s future plans include a data platform where members can share data sets and online interest groups, which will allow members to discuss their research interests with others.

There’s already evidence T-CAIREM is filling an important gap in Toronto’s burgeoning AI-in-medicine community. This past summer, an initial call for researchers to join the centre resulted in nearly 400 new members and the team is looking forward to adding even more to its growing community from students and researchers who are members of U of T and affiliated institutions.

“Our first priority is to build a strong community in the Toronto area and then collaborate extensively globally,” says Mamdani. “By bringing together brilliant clinicians and researchers and making it easier for them to collaborate and access data, we hope to enable advances in AI in healthcare that will radically change how we interact with the health-care system, the care we receive and the outcomes we achieve for future generations to come.”