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Over the past few years, the AI boom has transformed the way we live and work. AI has become a central topic of conversation and has been adopted and integrated across nearly every industry. 

This includes health care. Engineering researchers and industry experts discussed the ways AI is already reshaping cardiovascular care at the recent   Schulich Connects panel discussion, “Smart Health: Transforming Cardiovascular Care with Imaging and AI.”  

The panel weighed in on AI-driven cardiovascular imaging and how it is transforming the way we understand and manage heart health. The discussion was moderated by , PhD, associate head of research with the Department of Biomedical Engineering.

The impact of AI on cardiovascular care 

Some changes brought by AI are obvious; others are happening quietly in the background.

“In cardiovascular care, the advances are largely behind the scenes,” Rinker says in a post-panel interview.

Clinical workflows are becoming faster and more efficient, with AI helping teams interpret far more information than before. “There are many different ways that AI is changing how we deliver cardiovascular care," panellist , MD, director of precision medicine with the at the (CSM), says in an interview. 

"Right now, we’re using tools that are helping us do daily repetitive tasks, but soon it will help us make better clinical decisions” 

The added insight from AI being able to process more data gives clinicians a clearer picture of a patient’s health and allows them to respond sooner, guide next steps more effectively and shift diagnostics toward proactive prevention.

“The impact that AI will have on patient care delivery over the next decade is difficult to estimate — but we anticipate it will be highly disruptive,” says White.

Panellist , PhD, a biomedical engineering professor and entrepreneur in cardiovascular diagnostics, highlighted how AI can reveal previously invisible insights. 

“With AI, we’re now able not only to see pictures of the heart, but also how it works and how it evolves over time — whether with healthy aging or the onset of disease,” Di Martino says in a post-event interview.

“Being able to recognize these changes is one of the most exciting parts of AI for me right now.”

Improving access and reducing wait times

Access to timely cardiovascular imaging emerged as a key concern during the audience Q&A, particularly as demand continues to rise while resources remain fixed. One audience member pointed to the long wait times for cardiac MRI in ��֦��Ƶ and questioned the value of advanced imaging when patients must wait considerable time for answers.

White acknowledged the challenge, noting that the demand for cardiac imaging has grown rapidly in recent years. While ��֦��Ƶ already performs more cardiac MRIs per capita than anywhere else in Canada, he said the system is feeling the strain. 

“There’s been a tremendous growth in need with fixed resources,” White said. “So, the question becomes: How do we leverage AI to solve that problem?”

Panellists emphasized that AI can help address access challenges by guiding how limited imaging resources are allocated — supporting more targeted use of MRIs and helping prioritize patients who need them most.

AI is also improving access by increasing imaging efficiency. Panellist Estee Lee, MSc’14, director of research commercialization at , described how advances in image acquisition have significantly reduced scan times. “Image acquisition that used to take 40 minutes can now be reduced to 15 or 20 minutes,” allowing more patients to be scanned each day, Lee said.

 

Challenges and building trust

The panellists underscored that addressing access challenges will require technological innovation and trust, ensuring AI tools are adopted in ways that improve patient care while making the best use of limited health-care resources.

While the promise of AI in cardiovascular care is significant, panellists agreed careful oversight is essential as these tools are integrated into health-care systems. Data privacy, regulatory requirements and transparency remain key considerations, particularly as AI becomes more embedded in clinical decision making. Navigating these challenges is a core mission of the , a newly formed CSM facility led by White aimed at facilitating ethical data access, cross-faculty innovation, and clinical adoption of AI-driven medical imaging technology. 

White emphasized the importance of trust and explainability. “I don’t want to use a tool if I don’t understand how it arrived at a decision,” he says in a post-event interview, noting that clinicians and patients, alike, need clarity on how AI-generated recommendations are made.

Adoption also depends on ensuring AI supports — rather than replaces — clinical expertise. Di Martino highlighted that regulatory bodies view AI as an augmentative tool, requiring physicians to interpret and contextualize its outputs. Building that trust, panellists agreed, will take time, education, and continued collaboration between clinicians, engineers and innovators.