Acute myocardial infarction (AMI) is one of the major causes of morbidity and mortality
worldwide. The inflammation response during and after AMI is common and seems to play a�…

Abstract Purpose of Review This review of the literature aims to present potential
applications of radiomics in cardiovascular radiology and, in particular, in cardiac imaging�…

Rapid diagnosis of the Covid-19 disease is the best way to prevent infection. In this paper, it
is proposed to use machine learning methods to aid diagnoses quickly Covid-19 and�…

This study was aimed to investigate the predictive value of the radiomics features extracted
from pericoronaric adipose tissue—around the anterior interventricular artery (IVA)—to�…

Background Patients with type 2 diabetes mellitus (T2DM) are highly susceptible to
cardiovascular disease, and coronary artery disease (CAD) is their leading cause of death�…

In healthcare, the decision-making process is crucial, including COVID-19 prevention
methods should include fast diagnostic methods. Computed tomography (CT) is used to�…

Rationale and Objectives To compare the prediction performance of the epicardial adipose
tissue (EAT) and pericoronary adipose tissue (PCAT) radiomics models based on coronary�…

Cardiovascular disease remains the leading cause of death and disability for patients across
the world. Our understanding of atherosclerosis as a primary cholesterol issue has�…

Radiomics is the process of extracting useful quantitative features of high-dimensional data
that allows for automated disease classification, including atherosclerotic disease. Hence�…

Pericoronary adipose tissue (PCAT) features on Computed Tomography (CT) have been
shown to reflect local inflammation and increased cardiovascular risk. Our goal was to�…