Cardiovascular disease remains the leading cause of death in women. Given accumulating
evidence on sex-and gender-based differences in cardiovascular disease development and …

Artificial intelligence (AI) describes the use of computational techniques to perform tasks that
normally require human cognition. Machine learning and deep learning are subfields of AI …

This study explores the interlink between AI capabilities and circular business models
(CBMs) through a literature review. Extant literature reveals that AI can act as efficiency …

In the medical literature, promising results regarding accuracy of medical AI are presented
as claims for its potential to increase efficiency. This elision of concepts is misleading and …

Machine learning has become a key driver of the digital health revolution. That comes with a
fair share of high hopes and hype. We conducted a scoping review on machine learning in …

Artificial intelligence (AI) refers to the use of computational techniques to mimic human
thought processes and learning capacity. The past decade has seen a rapid proliferation of …

Radiomics, via the extraction of quantitative information from conventional radiologic
images, can identify imperceptible imaging biomarkers that can advance the …

Clinical and economic burdens exist within the coronary artery disease (CAD) care pathway
despite advances in diagnosis and treatment and the increasing utilization of percutaneous …

Advancements in artificial intelligence (AI) have rapidly transformed various sectors, and the
field of echocardiography is no exception. AI-driven technologies hold immense potential to …

Background Epicardial adipose tissue (EAT) has been considered as one of the probable
triggers of atrial fibrillation (AF). CT‐rediomics is a perspective noninvasive method of …