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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Nov 16, 2023
Date Accepted: Apr 19, 2024
Date Submitted to PubMed: May 20, 2024

The final, peer-reviewed published version of this preprint can be found here:

Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations

Zhu L, Mou W, Wu K, Lai Y, Lin A, Yang T, Zhang J, Luo P

Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations

J Med Internet Res 2024;26:e54607

DOI: 10.2196/54607

PMID: 38764297

PMCID: 11237788

Multimodal ChatGPT-4V for ECG Interpretation: Promise and Limitations

  • Lingxuan Zhu; 
  • Weiming Mou; 
  • Keren Wu; 
  • Yancheng Lai; 
  • Anqi Lin; 
  • Tao Yang; 
  • Jian Zhang; 
  • Peng Luo

ABSTRACT

Electrocardiogram (ECG) interpretation is an essential skill in cardiovascular medicine. This study evaluated the capabilities of newly released ChatGPT-4V, a large language model with visual recognition abilities, in interpreting ECG waveforms and answering related multiple-choice questions. A total of 62 ECG-related multiple-choice questions were collected from reputable medical exams. ChatGPT was prompted to answer the questions by analyzing the accompanying ECG images. Requiring at least 1 of 3 responses to be correct, ChatGPT achieved an overall accuracy of 83.87% across all question types. ChatGPT demonstrated significantly lower performance on counting-based questions like calculating QT intervals compared to diagnostic and treatment recommendation questions. The findings indicate that while ChatGPT shows promising potential in ECG interpretation and decision-making, its diagnostic reliability and quantitative analysis abilities need improvement before real clinical use. Further large-scale studies are warranted to fully evaluate ChatGPT's capabilities and track its progress as the model accumulates more medical knowledge through ongoing training. With technological advancements, multimodal AI like ChatGPT may one day play an important role in assisting clinicians with ECG interpretation and cardiovascular care.


 Citation

Please cite as:

Zhu L, Mou W, Wu K, Lai Y, Lin A, Yang T, Zhang J, Luo P

Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations

J Med Internet Res 2024;26:e54607

DOI: 10.2196/54607

PMID: 38764297

PMCID: 11237788

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