Importance Artificial intelligence (AI), driven by advances in deep learning (DL), has the
potential to reshape the field of cardiovascular imaging (CVI). While DL for CVI is still in its …

Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is
known about the phenotypic and genetic links of heart-brain systems. We quantified heart …

Medical datasets and especially biobanks, often contain extensive tabular data with rich
clinical information in addition to images. In practice, clinicians typically have less data, both …

UK Biobank is an intensively characterized prospective study of 500 000 men and women,
aged 40 to 69 years when recruited, between 2006 and 2010, from the general population of …

Aims We evaluated the associations of left atrial (LA) structure and function with prevalent
and incident cardiovascular disease (CVD), independent of left ventricular (LV) metrics, in …

We developed a novel interpretable biological heart age estimation model using
cardiovascular magnetic resonance radiomics measures of ventricular shape and …

Background Cardiac magnetic resonance native T1-mapping provides noninvasive,
quantitative, and contrast-free myocardial characterization. However, its predictive value in …

Abstract Background Coronavirus disease 2019 (COVID-19) disproportionately affects older
people. Observational studies suggest indolent cardiovascular involvement after recovery …

The predictive performance of polygenic scores (PGS) is largely dependent on the number
of samples available to train the PGS. Increasing the sample size for a specific phenotype is …

Importance Epicardial and pericardial adipose tissue (EPAT) has been associated with
cardiovascular diseases such as atrial fibrillation or flutter (AF) and coronary artery disease …