OVERVIEW

American Board of Artificial Intelligence in Medicine (ABAIM) AI in Cardiology is organized by American Board of Artificial Intelligence in Medicine (ABAIM) and will be held on Aug 08, 2026.

Description:
Artificial Intelligence for Cardiologists, Cardiac Surgeons, and Cardiac Clinicians is a cutting-edge, one-day virtual seminar tailored for physicians, surgeons, and advanced cardiac professionals who want to lead the AI transformation in cardiovascular care. This highly interactive course explores the most relevant applications of AI in clinical cardiology and cardiac surgery — from imaging and diagnostics to digital twins and generative models.

Whether you’re just beginning to explore AI or looking to deepen your expertise, this course will empower you with practical knowledge and critical frameworks to responsibly and effectively integrate AI into your practice.

This fast-paced, case-based course will answer all of the following questions and more:

How are AI models currently improving risk prediction, diagnostics, and treatment planning in cardiovascular medicine?
What are the strengths and limitations of model evaluation metrics like accuracy, sensitivity, and ROC curves?
What are “digital twins,” and how can they improve personalized cardiac care?
How should clinicians collaborate with data scientists and evaluate emerging AI tools and research?
What are the ethical and legal concerns surrounding AI in cardiology?

Learning Objectives include:

Understanding core AI concepts such as ML, DL, and LLMs in the context of cardiovascular care
Identifying current clinical applications of AI in cardiac imaging, EP, and heart failure
Evaluating model performance and avoiding common pitfalls such as bias and overfitting
Navigating ethical, legal, and regulatory issues, including patient privacy and explainability
Exploring the role of autonomous agents and generative AI in clinical workflows
Applying a critical lens to AI research and vendor tools
Understanding digital twins and their role in predictive, personalized cardiac care
Collaborating effectively with data science teams
Preparing for emerging AI trends and the evolving role of the clinician in the AI era