Effectiveness of the GPT-4o Model in Interpreting Electrocardiogram Images for Cardiac Diagnostics: Diagnostic Accuracy Study.

ABSTRACT: Recent progress has demonstrated the potential of deep learning models in analyzing electrocardiogram (ECG) pathologies. However, this method is intricate, expensive to develop, and designed for specific purposes. Large language models show promise in medical image interpretation, and yet their effectiveness in ECG analysis remains understudied. Generative Pretrained Transformer 4 Omni (GPT-4o), a multimodal artificial intelligence model, capable of processing images and text without task-specific training, may offer an accessible alternative. This study aimed to evaluate GPT-4o's effectiveness in interpreting 12-lead ECGs, assessing classification accuracy, and exploring methods to enhance its performance. A total of 6 common ECG diagnoses were evaluated: normal ECG, ST-segment elevation

SUBMITTER: Engelstein H 

PROVIDER: S-EPMC12375907 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature