Rapid technological advances in non-invasive imaging, coupled with the availability of large
data sets and the expansion of computational models and power, have revolutionized the …

Recent advances in artificial intelligence (AI) for cardiac computed tomography (CT) have
shown great potential in enhancing diagnosis and prognosis prediction in patients with …

Having a reliable approximation of heating load (HL) and cooling load (CL) is a substantial
task for evaluating the energy performance of buildings (EPB). Also, the appearance of soft …

Many studies have shown that epicardial fat is associated with a higher risk of heart
diseases. Accurate epicardial adipose tissue quantification is still an open research issue …

The present review summarizes the available evidence on artificial intelligence (AI)
algorithms aimed to the segmentation of epicardial and pericardial adipose tissues on …

The present study aims to assess the superiority of the metaheuristic evolutionary when
compared to the conventional machine learning classification techniques for landslide …

Inversion of temperature and species concentration distributions from radiometric
measurements involves solving nonlinear, ill-posed and high-dimensional problems …

The main effort of this study is to examine the feasibility of four novel machine learning
models namely Alternating Model Tree, Random Tree, Least Median Square, and Multi …

Background Artificial intelligence (AI) technology has been increasingly developed and
studied in cardiac imaging. This systematic review summarizes the latest progress of image …

The epicardial fat plays a key role in the development of many cardiovascular diseases. It is
necessary and useful to precisely segment this fat from CT scans in clinical studies …