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 …

Directed by 2 decades of technological processes and remodeling, the dynamic quality of
healthcare data combined with the progress of computational power has allowed for rapid …

Abstract Purpose of Review In this review, we aim to summarize state-of-the-art artificial
intelligence (AI) approaches applied to cardiovascular CT and their future implications …

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 …

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 …

Rapid development of artificial intelligence (AI) is gaining grounds in medicine. Its huge
impact and inevitable necessity are also reflected in cardiovascular imaging. Although AI …

The collection of large, heterogeneous electronic datasets and imaging from patients with
cardiovascular disease (CVD) has lent itself to the use of sophisticated analysis using …

The arrival of artificial intelligence (AI) in cardiovascular medicine has introduced many new
words and concepts to our dictionary. AI is already being used as part of medical software to …

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 …

Artificial intelligence (AI) promises to revolutionize many fields, but its clinical
implementation in cardiovascular imaging is still rare despite increasing research. We …