Background Interest in the application of machine learning (ML) to the design, conduct, and
analysis of clinical trials has grown, but the evidence base for such applications has not …

Cardiovascular disease (CVD) is the principal cause of mortality and morbidity globally. With
the pressures for improved care and translation of the latest medical advances and …

Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of
various types but most often to deep neural networks. Cardiology is at the forefront of AI in …

Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of
intense exploration, showing potential to automate human tasks and even perform tasks …

Abstract Machine learning and artificial intelligence are generating significant attention in
the scientific community and media. Such algorithms have great potential in medicine for …

Aims Symptom-based pretest probability scores that estimate the likelihood of obstructive
coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to …

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 …

Abstract Machine learning (ML) is a sub-field of artificial intelligence that uses computer
algorithms to extract patterns from raw data, acquire knowledge without human input, and …

Machine learning (ML), a branch of artificial intelligence, where machines learn from big
data, is at the crest of a technological wave of change sweeping society. Cardiovascular …

The field of cardiac electrophysiology (EP) had adopted simple artificial intelligence (AI)
methodologies for decades. Recent renewed interest in deep learning techniques has …