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 risk of coronary heart disease (CHD) clinical manifestations and patient management is
estimated according to risk scores accounting multifactorial risk factors, thus failing to cover …

Background Studies have rarely investigated stenosis detection from head and neck CT
angiography scans because accurate interpretation is time consuming and labor intensive …

Purpose The purpose of this study was to evaluate the capabilities of photon-counting (PC)
CT combined with artificial intelligence-derived coronary computed tomography …

Currently, clinically available coronary CT angiography (CCTA) derived fractional flow
reserve (CT-FFR) is time-consuming and complex. We propose a novel artificial intelligence …

Abstract ST-Segment Elevation Myocardial Infarction (STEMI) is a life-threatening medical
emergency characterized by complete coronary artery occlusion, leading to myocardial …

The future paradigm of early cardiac diagnostics is shifting the focus towards heart attack
preventive medicine based on non-invasive medical imaging with the support of artificial …

Objectives To investigate the effect of reader experience, calcification and image quality on
the performance of deep learning (DL) powered coronary CT angiography (CCTA) in …

Background Transcatheter arterial chemoembolization (TACE) is the mainstay of therapy for
intermediate-stage hepatocellular carcinoma (HCC); yet its efficacy varies between patients …

Purpose The purpose of this study was to evaluate the diagnostic performance of automated
deep learning in the detection of coronary artery disease (CAD) on photon-counting …