Cardiac imaging plays an important role in the diagnosis of cardiovascular disease (CVD).
Until now, its role has been limited to visual and quantitative assessment of cardiac structure …

Artificial intelligence (AI)-based applications have found widespread applications in many
fields of science, technology, and medicine. The use of enhanced computing power of …

Aims We tested the hypothesis that a machine learning (ML) algorithm utilizing both complex
echocardiographic data and clinical parameters could be used to phenogroup a heart failure …

Healthcare, conceivably more than any other area of human endeavour, has the greatest
potential to be affected by artificial intelligence (AI). This potential has been shown by …

Background Stress testing helps diagnose heart failure with preserved ejection fraction
(HFpEF), but there are no established criteria for quantifying left ventricular (LV) functional …

The echocardiogram is a test that is widely used in Heart Disease Diagnoses. However, its
analysis is largely dependent on the physician's experience. In this regard, artificial …

In routine clinical practice, the diagnosis and treatment of cardiovascular disease (CVD) rely
on data in a variety of formats. These formats comprise invasive angiography, laboratory …

The number of cardiovascular imaging studies is growing exponentially, and so is the need
to improve clinical workflow efficiency and avoid missed diagnoses. With the availability and …

Background Echocardiography provides complex data on cardiac function that can be
integrated into patterns of dysfunction related to the severity of cardiac disease. The aim of …

Information about myocardial motion and deformation is key to differentiate normal and
abnormal conditions. With the advent of approaches relying on data rather than pre …