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Guido Marchi¹, Giulia Gambini², Giacomo Guglielmi³

¹UO Pneumologia, Dipartimento Cardio-Toraco-Vascolare, Azienda ospedaliero-universitaria Pisana, Pisa.

Recenti Progressi in Medicina

|October 2, 2025

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Three large language models (LLMs) were tested on Chronic Obstructive Pulmonary Disease (COPD) questions. Gemini 1.5 Advanced excelled in completeness, while Claude 3.5 Sonnet led in accuracy and terminology for COPD patient education.

Area of Science:

Artificial Intelligence in Medicine
Respiratory Medicine
Medical Education Technology

Background:

Large language models (LLMs) show potential for medical information dissemination.
Accurate and safe patient education is crucial for managing Chronic Obstructive Pulmonary Disease (COPD).
Evaluating LLM performance on established clinical guidelines is necessary.

Purpose of the Study:

To assess the performance of three leading LLMs (ChatGPT-4, Claude 3.5 Sonnet, Gemini 1.5 Advanced) in answering COPD-related questions.
To compare AI-generated responses based on completeness, accuracy, terminology, accessibility, and safety.
To evaluate the suitability of LLMs for COPD patient education.

Main Methods:

Utilized 61 COPD-related questions derived from GOLD recommendations.

Related Experiment Videos

Generated 90 AI responses using ChatGPT-4, Claude 3.5 Sonnet, and Gemini 1.5 Advanced.

Evaluated responses by 61 pulmonologists across 6 continents using a standardized rating scale.

Main Results:

Gemini 1.5 Advanced demonstrated superior completeness in responses.
Claude 3.5 Sonnet achieved higher ratings for accuracy and appropriate terminology.
No significant differences were observed among the LLMs regarding accessibility and safety.

Conclusions:

LLMs show promise for supporting COPD patient education.
Clinical implementation requires careful consideration and further validation for safety and accuracy.
Expert review is essential to ensure reliable AI-generated medical information.