Deep learning-based prediction for significant coronary artery stenosis on coronary computed tomography angiography in asymptomatic populations.

ABSTRACT:

Background

Although coronary computed tomography angiography (CCTA) is currently utilized as the frontline test to accurately diagnose coronary artery disease (CAD) in clinical practice, there are still debates regarding its use as a screening tool for the asymptomatic population. Using deep learning (DL), we sought to develop a prediction model for significant coronary artery stenosis on CCTA and identify the individuals who would benefit from undergoing CCTA among apparently healthy asymptomatic adults.

Methods

We retrospectively reviewed 11,180 individuals who underwent CCTA as part of routine health check-ups between 2012 and 2019. The main outcome was the presence of coronary artery stenosis of ≥70% on CCTA. We developed a prediction model using machine learning (ML), i

SUBMITTER: Lee H 

PROVIDER: S-EPMC10320158 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature