Jagat Narula a, 1, Y. Chandrashekhar b, 1, Amir Ahmadi a, Suhny Abbara c, Daniel S.
Berman d, Ron Blankstein e, Jonathon Leipsic f, David Newby g, Edward D. Nicol h, Koen …

CT based technologies have evolved considerably in recent years. Coronary CT
angiography (CTA) provides robust assessment of coronary artery disease (CAD). Early …

Aims Traditional prognostic risk assessment in patients undergoing non-invasive imaging is
based upon a limited selection of clinical and imaging findings. Machine learning (ML) can …

Background: Optimal management of patients with stable chest pain relies on the prognostic
information provided by noninvasive cardiovascular testing, but there are limited data from …

Coronary artery disease (CAD) remains the leading cause of mortality and morbidity in
developed countries. In patients presenting with acute coronary syndromes (ACS), timely …

Cardiopulmonary diseases are major causes of death worldwide, but currently
recommended strategies for diagnosis and prevention may be outdated because of recent …

Background—The contribution of plaque extent to predict cardiovascular events among
patients with nonobstructive and obstructive coronary artery disease (CAD) is not well …

Objectives: The goal of this study was to use machine learning to more accurately predict
survival after echocardiography. Background: Predicting patient outcomes (eg, survival) …

Background The recent development of artificial intelligence–guided quantitative coronary
computed tomography angiography analysis (AI-QCT) has enabled rapid analysis of …

Objectives: This study sought to determine updated conversion factors (k-factors) that would
enable accurate estimation of radiation effective dose (ED) for coronary computed …