Artificial Intelligence for Opportunistic Screening of Cardiovascular Disease

GRAND ROUND OBJECTIVES

• Understand the role of coronary artery calcium (CAC) in enhancing atherosclerotic cardiovascular disease (ASCVD) risk assessment and guiding statin therapy decisions.
• Explore the application of deep learning algorithms for quantifying incidental CAC in non-gated CT scans and its potential impact on statin prescription rates.
• Evaluate the potential of artificial intelligence in improving opportunistic ASCVD screening and identify areas for future research focusing on clinical outcomes and health equity.

ACCREDITATION FOR CARDIOVASCULAR GRAND ROUNDS

The University of Washington School of Medicine is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The University of Washington School of Medicine designates this live activity for a maximum of 36.0 AMA PRA Category 1 Credits.

Physicians should claim only the credit commensurate with the extent of their participation in the activity. (Each session is 1.0 credit)

To request disability accommodation, contact the Office of the Disability Services Office at least ten days in advance of the event at 206-543-6450 (voice), 206-543-6452 (TTY), 206-685-7264 (FAX), dso@u.washington.edu.