ChatGPT response consistency to the 2025 ESC/EACTS guidelines for the management of valvular heart disease: A test–retest study using binary and multiple-choice questions - Summary - MDSpire
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ChatGPT response consistency to the 2025 ESC/EACTS guidelines for the management of valvular heart disease: A test–retest study using binary and multiple-choice questions
To evaluate the level of agreement and temporal performance of AI-based ChatGPT with the 2025 ESC/EACTS GMVHD in supporting clinicians with essential knowledge in valvular heart disease (VHD).
Key Findings:
The study aimed to assess the consistency of ChatGPT responses with established guidelines for VHD management, covering diagnostic, follow-up, and therapeutic decision-making processes.
Inter-rater agreement was achieved for all evaluated items.
Interpretation:
The study seeks to contribute to the literature on AI applications in cardiology, particularly in the context of VHD management, by providing insights into the reliability of AI-generated responses.
Limitations:
The study did not evaluate health equity or AI performance across diverse populations.
Potential biases in question design and evaluation may exist, which could affect the results.
Conclusion:
The findings will help assess the usability of ChatGPT as a clinical decision-support tool for VHD management.
