Diagnostic accuracy of ChatGPT for 12-lead ECG-based localisation of ventricular ectopic foci prior to catheter ablation.

ABSTRACT:

Background

Precise pre-procedural localisation of ventricular ectopic (VE) foci shortens mapping time, reduces fluoroscopy, and improves ablation success. Large language models such as ChatGPT offer instant, free-text clinical support; however, their accuracy in ECG-based VE localisation is unknown.

Methods

In this single-centre pilot study, we assessed the diagnostic accuracy of ChatGPT in 50 consecutive adults (average age: 43 ± 14 years; 58% women) scheduled for first-time VE ablation. ChatGPT served as the index test, and invasive electroanatomical mapping during the ablation served as the reference standard. A blinded electrophysiologist converted each index 12-lead ECG into a structured textual description of QRS morphology. ChatGPT-4o (temperature 0.2) was then tasked

SUBMITTER: Gurses KM 

PROVIDER: S-EPMC12833440 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature