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

Cardiovascular diseases (CVDs) remain a major global health challenge, leading to
significant morbidity and mortality while straining healthcare systems. Despite progress in …

Background Use of artificial intelligence (AI) in cardiovascular imaging may potentially
augment clinical decision-making in disease management, but no prospective randomized …

Introduction and Hypothesis The aim was to conduct a scoping review of the literature on the
use of machine learning (ML) in female urinary incontinence (UI) over the last decade …

Background: Artificial intelligence (AI) can radically change almost every aspect of the
human experience. In the medical field, there are numerous applications of AI and …

Infarct size (IS) is the most robust end point for evaluating the success of preclinical studies
on cardioprotection. The gold standard for IS quantification in ischemia/reperfusion (I/R) …

Background Extracting phenotype-representative flow patterns and their associated
numerical metrics is a bottleneck in the clinical translation of advanced cardiac flow imaging …

Echocardiography is a versatile imaging technique used mainly by sonographers and
cardiologists that have accomplished several years of training to appropriately acquire and …

Achieving optimal cardiovascular health in rural populations can be challenging for several
reasons including decreased access to care with limited availability of imaging modalities …

Background: Extracting explainable flow metrics is a bottleneck to the clinical translation of
advanced cardiac flow imaging modalities. We hypothesized that reduced-order models …