Health professionals are encouraged to take the Guidelines fully into account when
exercising their clinical judgment, as well as in the determination and the implementation of …

The global prevalence of diabetes is predicted to increase dramatically in the coming
decades as the population grows and ages, in parallel with the rising burden of overweight …

Data science is likely to lead to major changes in cardiovascular imaging. Problems with
timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The …

Heart failure is a complex clinical syndrome, the incidence and prevalence of which is
increased in diabetes mellitus, pre-diabetes, and obesity. Although this may arise from …

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 …

Ejection fraction (EF) reflects both cardiac function and remodeling, and is widely
recognized as a valuable diagnostic and prognostic tool. Its use in a variety of settings …

Background Heterogeneity in type 2 diabetes presentation and progression suggests that
precision medicine interventions could improve clinical outcomes. We undertook a …

The measurement of left ventricular ejection fraction (LVEF) is a ubiquitous component of
imaging studies used to evaluate patients with cardiac conditions and acts as an arbiter for …

Diabetes mellitus (DM) significantly increases the risk of heart disease, and DM-related
healthcare expenditure is predominantly for the management of cardiovascular …

Importance The cornerstones of imaging in heart failure (HF) are the measurement of
systolic and diastolic function and left ventricular (LV) filling pressure. Observations Ejection …