Artificial intelligence applications have shown success in different medical and health care
domains, and cardiac imaging is no exception. However, some machine learning models …

Background Cardiovascular diseases (CVD) affect over half a billion people worldwide and
are the leading cause of global deaths. In particular, due to population aging and worldwide …

Cardiovascular ageing is a process that begins early in life and leads to a progressive
change in structure and decline in function due to accumulated damage across diverse cell …

Cardiovascular diseases remain a significant health burden, with imaging modalities like
echocardiography, cardiac computed tomography, and cardiac magnetic resonance …

Chronological age is an imperfect measure of the aging process, which is affected by a wide
range of genetic and environmental exposures. Biological age estimates may be derived …

Population aging is one of the most important demographic transformations of our time.
Increasing the “health span”—the proportion of life spent in good health—is a global priority …

Background DNA methylation (DNAm) age acceleration (AgeAccel) and cardiac age by 12-
lead advanced electrocardiography (A-ECG) are promising biomarkers of biological and …

Background There is a paucity of data on artificial intelligence-estimated biological
electrocardiography (ECG) heart age (AI ECG-heart age) for predicting cardiovascular …

Background Existing research demonstrates the association of shorter leukocyte telomere
length with increased risk of age‐related health outcomes including cardiovascular …

Biological age is a personalized measure of the health status of an organism, organ, or
system, as opposed to simply accounting for chronological age. To date, there have been …