Although radiomics research has experienced rapid growth in recent years, with numerous
studies dedicated to the automated extraction of diagnostic and prognostic information from …

Radiomics represents the science of extracting and analyzing a multitude of quantitative
features from medical imaging, revealing the quantitative potential of radiologic images. This …

Objectives To prospectively investigate whether fully automated artificial intelligence (FAAI)-
based coronary CT angiography (CCTA) image processing is non-inferior to semi …

Background Radiomics is not yet used in clinical practice due to concerns regarding its
susceptibility to technical factors. We aimed to assess the stability and interscan and …

Rationale and Objectives This study aims to evaluate the capability of machine learning
algorithms in utilizing radiomic features extracted from cine-cardiac magnetic resonance …

Ischemic stroke is a leading global cause of death and disability and is expected to rise in
the future. The present diagnostic techniques, like CT and MRI, have some limitations in …

Coronary computed tomography angiography (CCTA) is a powerful tool to rule out coronary
artery disease (CAD). In the last decade, myocardial perfusion CT (CTP) technique has …

About 5% of annual access to emergency departments (EDs) and up to 25–30% of hospital
admissions involve patients with symptoms suggestive of acute coronary syndrome (ACS) …

Background Aortic dissection is a life-threatening clinical emergency, but it is often missed
and misdiagnosed due to the limitations of diagnostic technology. In this study, we …

The integration of computational technologies into cardiology has significantly advanced the
diagnosis and management of cardiovascular diseases. Computational cardiology …