Technical advances in artificial intelligence (AI) in cardiac imaging are rapidly improving the
reproducibility of this approach and the possibility to reduce time necessary to generate a …

The diagnostic evaluation of coronary artery disease is undergoing a dramatic
transformation with a new focus on atherosclerotic plaque. This review details the evidence …

Objectives To calculate the coronary artery calcification score (CACS) obtained from
coronary artery computed tomography angiography (CCTA) examination and combine it …

The technological development of Artificial Intelligence (AI) has grown rapidly in recent
years. The applications of AI to cardiovascular imaging are various and could improve the …

The tremendous advances in digital information and communication technology have
entered everything from our daily lives to the most intricate aspects of medical and surgical …

Research into machine learning (ML) for clinical vascular analysis, such as those useful for
stroke and coronary artery disease, varies greatly between imaging modalities and vascular …

Ischemic chronic cardiomyopathy (ICC) is still one of the most common cardiac diseases
leading to the development of myocardial ischemia, infarction, or heart failure. The …

Purpose To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting
hemodynamically significant coronary artery disease (CAD) by using a rest dataset of …

Atherosclerotic cardiovascular disease (ASCVD) is the most common cause of death
globally. Increasing amounts of highly diverse ASCVD data are becoming available and …

Background Machine learning (ML) has shown promise in improving the risk prediction in
non-invasive cardiovascular imaging, including SPECT MPI and coronary CT angiography …