This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on the development of cardiovascular diseases (CVD) risk, its underlying determinants, and to construct precise predictive models capable of accurately ...
Journal of the American College of Cardiology
Nov 12, 2024
Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials are expensive, lengthy, and insufficiently diverse. Emerging artificial intelligence (AI) technolog...
BACKGROUND: Artificial intelligence (AI)-enabled electrocardiography (ECG) can be used to predict risk of future disease and mortality but has not yet been adopted into clinical practice. Existing model predictions do not have actionability at an ind...
IMPORTANCE: Risk estimation is an integral part of cardiovascular care. Local recalibration of guideline-recommended models could address the limitations of existing tools.
European heart journal. Cardiovascular Imaging
Sep 30, 2024
AIMS: Standard methods of heart chamber volume estimation in cardiovascular magnetic resonance (CMR) typically utilize simple geometric formulae based on a limited number of slices. We aimed to evaluate whether an automated deep learning neural netwo...
For World Heart Day on September 24, 2024, the World Heart Federation urges nations to endorse national strategies for enhancing cardiovascular health. While advancements show promise in reducing atherosclerosis, addressing healthcare inequalities an...
Scandinavian journal of medicine & science in sports
Sep 1, 2024
Step cadence-based and machine-learning (ML) methods have been used to classify physical activity (PA) intensity in health-related research. This study examined the association of intensity-specific PA duration with all-cause (ACM) and CVD mortality ...
Diabetes/metabolism research and reviews
Sep 1, 2024
AIMS: To examine whether sublingual microcirculation can be used as an effective and noninvasive method for assessing cardiovascular, kidney, and metabolic risks in patients with type 2 diabetes mellitus (T2DM).