Multi-modal artificial intelligence algorithm for the prediction of left atrial low-voltage areas in atrial fibrillation patient based on sinus rhythm electrocardiogram and clinical characteristics: a retrospective, multicentre study.

ABSTRACT:

Aims

We aimed to develop an artificial intelligence (AI) algorithm capable of accurately predicting the presence of left atrial low-voltage areas (LVAs) based on sinus rhythm electrocardiograms (ECGs) in patients with atrial fibrillation (AF).

Methods and results

The study included 1133 patients with AF who underwent catheter ablation procedures, with a total of 1787 12-lead ECG images analysed. Artificial intelligence-based algorithms were used to construct models for predicting the presence of LVAs. The DR-FLASH and APPLE clinical scores for LVAs prediction were calculated. A receiver operating characteristic (ROC) curve and a calibration curve were used to evaluate model performance. Multicentre validation included 92 AF patients from five centres, with a total of 174 ECG

SUBMITTER: Tao Y 

PROVIDER: S-EPMC11914728 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature