The application of artificial intelligence (AI) to the electrocardiogram (ECG), a ubiquitous and
standardized test, is an example of the ongoing transformative effect of AI on cardiovascular …

Artificial intelligence (AI) has given the electrocardiogram (ECG) and clinicians reading them
super-human diagnostic abilities. Trained without hard-coded rules by finding often …

Although artificial intelligence (AI) algorithms have been shown to be capable of identifying
cardiac dysfunction, defined as ejection fraction (EF)≤ 40%, from 12-lead …

Recent artificial intelligence (AI) advancements in cardiovascular care offer potential
enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on …

Background Valvular heart disease is an important contributor to cardiovascular morbidity
and mortality and remains underdiagnosed. Deep learning analysis of electrocardiography …

Background Most patients who have heart failure with a reduced ejection fraction, when left
ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is …

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 possibilities and implementation of wearable cardiac monitoring beyond atrial fibrillation
are increasing continuously. This review focuses on the real-world use and evolution of …

Nowadays, the implementation of Artificial Intelligence (AI) in medical diagnosis has
attracted major attention within both the academic literature and industrial sector. AI would …

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