Artificial Intelligence Prediction of Age from Echocardiography as a Marker for Cardiovascular Disease.

ABSTRACT: Accurate understanding of biological aging and the impact of environmental stressors is crucial for understanding cardiovascular health and identifying patients at risk for adverse outcomes. Chronological age stands as perhaps the most universal risk predictor across virtually all populations and diseases. While chronological age is readily discernible, efforts to distinguish between biologically older versus younger individuals can, in turn, potentially identify individuals with accelerated versus delayed cardiovascular aging. This study presents a deep learning artificial intelligence (AI) approach to predict age from echocardiogram videos, leveraging 2,610,266 videos from 166,508 studies from 90,738 unique patients and using the trained models to identify features of accelerated and del

SUBMITTER: Rawlani M 

PROVIDER: S-EPMC11974980 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature