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Accès ouvert déclaré 2026 article

Is ChatGPT's Knowledge on Rhinology Accurate? Can It Be Utilized in Medical Education and Patient Information?

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Le résumé fourni par la source

ABSTRACT Objective: The ChatGPT is a new artificial intelligence model designed to create human-like chats. As a result of advancing knowledge and technological improvements, it is promising in the field of medicine, especially as a resource for patients and clinicians. The aim of our study was to measure the accuracy and consistency of ChatGPT answers to questions in the field of rhinology.Methods: In March 2024, ChatGPT (ChatGPT version 4) was presented with 130 rhinology questions. Each question was asked to ChatGPT twice, and the consistency and reproducibility of the answers were investigated. The answers were evaluated by three ENT physicians. Results:The answers given by the ChatGPT were consistent at a rate of 91.5%(119/130). Among the inconsistent answers, the second answer was found to be more correct in out of 10/11. Statistically, the second answer was more correct (p:0011). In 130 questions, as a result of the controller evaluation, the number of answers evaluated as completely correct was 99/81/80(76.2%, 62.3%, and 61.5%, respectively). However, completely incorrect answers were observed in 5.4%, 4.6%, and 5.4%, respectively. Accordingly, there was no statistically significant difference between the controllers(p:0.270).Conclusion:The inaccuracy of ChatGPT in patient information and education processes is considered acceptable and reliable. However, it is also seen that ChatGPT answers are not completely correct and can provide misleading answers to some questions. We believe that it would be safer and more accurate to use ChatGPT as an informative and educational tool for patients with the control of experts.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Is ChatGPT's Knowledge on Rhinology Accurate? Can It Be Utilized in Medical Education and Patient Information?
Date Crossref
26/03/2026
Éditeur
Türk Rinoloji Dernegi
Type
journal-article

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Les sujets associés

Artificial Intelligence in Healthcare and EducationClinical Reasoning and Diagnostic SkillsMachine Learning in Healthcare

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