Renowned Miller School Cardiologist Edits Special Journal Issue on Artificial Intelligence
Summary
- Dr. Yiannis Chatzizisis is co-editor of a Journal of the Society for Cardiovascular Angiography & Interventions issue on artificial intelligence in cardiovascular interventions.
- Dr. Chatzizisis leads a team at the Center for Digital Cardiovascular Innovations which looks at the role of AI to accelerate cardiovascular procedures to improve patient outcomes.
- While optimistic about AI’s contribution to cardiovascular medicine, Dr. Chatzizisis cautions it must be used with proper safeguards.
A renowned cardiologist at the University of Miami Miller School of Medicine is co-editor of a groundbreaking special issue of the Journal of the Society for Cardiovascular Angiography & Interventions (JSCAI) on the role of artificial intelligence (AI) in cardiovascular interventions.
The issue explores how artificial intelligence is revolutionizing cardiovascular clinical care, research, education and training, said Yiannis Chatzizisis, M.D., Ph.D., professor in the Division of Cardiovascular Medicine and chief of cardiology at the Miller School.
“AI offers the opportunity to address long-standing challenges and open new avenues for previously inconceivable ideas,” Dr. Chatzizisis said. “AI can help optimize procedural planning, improve patient outcomes, accelerate device development and enhance education, while breaking gaps in access to care. In fact, the greatest boon of AI is its potential to bridge the knowledge and skills gap in interventional cardiology by democratizing access to clinical expertise on a global scale.”
At the Miller School, Dr. Chatzizisis leads a team at the Center for Digital Cardiovascular Innovations, which looks at the role of AI and related technologies such as computational simulations and extended reality — collectively called AISER — to provide support for early decision-making and accelerate cardiovascular procedures to improve patient outcomes. He is also collaborating with industry to accelerate the research and development process for new cardiovascular devices.
AI Shaping Cardiology
In the special journal issue, Dr. Chatzizisis co-authored the lead editorial, “Revolutionizing Cardiovascular Interventions With Artificial Intelligence,” with issue guest editor Elazer Edelman, M.D, Ph.D.
“We are at an inflection point where AI is no longer a concept of the future but a critical tool shaping today’s clinical practice,” Dr. Edelman said. “This special issue aims to provide clinicians, researchers and industry leaders with insights into the capabilities, limitations and future directions of AI in cardiovascular interventions.”
Both guest editors noted that AI integration must be approached responsibly.
“As we embrace AI, we must also be mindful of its limitations, ensuring that human oversight remains central to its application in cardiovascular care,” Dr. Chatzizisis said. “This will require ongoing validation, rigorous data privacy protections and a commitment to addressing bias in AI-driven decision support systems.”
The JSCAI’s special issue examines AI’s role in several core areas of interventional cardiology, including:
• Intravascular imaging and optical coherence tomography: AI-powered imaging software enhances real-time visualization, automates plaque characterization and guides stent deployment with greater accuracy.
• Percutaneous coronary intervention optimization: AI-based decision support tools assist interventionalists in choosing the best treatment strategy based on patient-specific data, reducing complications and improving outcomes.
• Risk prediction models for procedural success: AI enables predictive analytics to assess a patient’s risk for restenosis, thrombosis or procedural failure, helping physicians tailor interventions accordingly.
• Robotics and automation in the cath lab: AI-driven robotic-assisted interventions are improving precision, reducing radiation exposure and enabling remote-controlled procedures.
• AI in structural heart disease: AI-powered imaging and computational models are optimizing transcatheter valve interventions, reducing procedural time and enhancing post-procedural assessment.
Another area of focus is the acceleration of cardiovascular device innovation through AI-powered trials, which have the potential to reduce development timelines and regulatory burdens, while ensuring patient safety by simulating device behavior.
“Many clinicians and researchers may not yet grasp the full scope of AI’s impact, and this special issue arrives at a pivotal moment to highlight its transformative potential,” said JSCAI’s editor-in-chief, Alexandra Lansky, M.D., M.S.C.A.I. “This issue is designed to be indispensable to practicing interventionalists.”
AI in Coronary Artery Interventions
Dr. Chatzizisis was also the lead author of a journal article, “Artificial Intelligence in Coronary Artery Interventions: Preprocedural Planning and Procedural Assistance,” with the Miller School’s Wei Wu, Ph.D., assistant professor of medicine, and Shijia Zhao, Ph.D., research assistant professor of medicine, and other co-authors.
The article explored the latest advancements of AI applications, such as identifying individuals at increased risk of coronary artery disease, preprocedural planning and real-time procedural guidance. It also addressed the major obstacles that hinder the widespread clinical adoption of AI technologies in this field.
“Many studies demonstrate promising improvements in diagnostic accuracy, risk prediction, procedural planning and outcome assessment, yet recurring limitations emphasize the need for robust validation studies and broader applicability,” Dr. Chatzizisis said. “But as AI continues to evolve, its applications in cardiovascular interventions will expand, fostering a future where predict cardiovascular events can be predicted before they occur, and expert-level personalized interventions can be delivered faster and more efficiently to every patient.”
Tags: AI, artificial intelligence, Cardiovascular Division, Dr. Yiannis Chatzizisis, interventional cardiology, technology