ChatGPT’s Response Consistency: A Study on Repeated Queries of Medical Examination Questions

GND
1330857674
ORCID
0009-0000-4316-4249
Zugehörigkeit
Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Jena, Friedrich Schiller University Jena, Am Klinikum 1, 07747 Jena, Germany;
Funk, Paul F.;
ORCID
0000-0002-3875-7389
Zugehörigkeit
Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich (TUM), Ismaningerstrasse 22, 81675 Munich, Germany(A.B.D.);(B.W.)
Hoch, Cosima C.;
Zugehörigkeit
Department of Plastic Surgery and Hand Surgery, Klinikum Rechts der Isar, Technical University of Munich (TUM), Ismaningerstrasse 22, 81675 Munich, Germany
Knoedler, Samuel;
Zugehörigkeit
Division of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
Knoedler, Leonard;
Zugehörigkeit
Department of Dermatology, Erasmus Medical Centre, Dr. Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
Cotofana, Sebastian;
Zugehörigkeit
Instituto Ivo Pitanguy, Hospital Santa Casa de Misericórdia Rio de Janeiro, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro 20020-022, Brazil;
Sofo, Giuseppe;
Zugehörigkeit
Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich (TUM), Ismaningerstrasse 22, 81675 Munich, Germany(A.B.D.);(B.W.)
Bashiri Dezfouli, Ali;
ORCID
0000-0002-3062-459X
Zugehörigkeit
Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich (TUM), Ismaningerstrasse 22, 81675 Munich, Germany(A.B.D.);(B.W.)
Wollenberg, Barbara;
ORCID
0000-0001-9671-0784
Zugehörigkeit
Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Jena, Friedrich Schiller University Jena, Am Klinikum 1, 07747 Jena, Germany;
Guntinas-Lichius, Orlando;
Zugehörigkeit
Department of Plastic Surgery and Hand Surgery, Klinikum Rechts der Isar, Technical University of Munich (TUM), Ismaningerstrasse 22, 81675 Munich, Germany
Alfertshofer, Michael

(1) Background: As the field of artificial intelligence (AI) evolves, tools like ChatGPT are increasingly integrated into various domains of medicine, including medical education and research. Given the critical nature of medicine, it is of paramount importance that AI tools offer a high degree of reliability in the information they provide. (2) Methods: A total of n = 450 medical examination questions were manually entered into ChatGPT thrice, each for ChatGPT 3.5 and ChatGPT 4. The responses were collected, and their accuracy and consistency were statistically analyzed throughout the series of entries. (3) Results: ChatGPT 4 displayed a statistically significantly improved accuracy with 85.7% compared to that of 57.7% of ChatGPT 3.5 ( p < 0.001). Furthermore, ChatGPT 4 was more consistent, correctly answering 77.8% across all rounds, a significant increase from the 44.9% observed from ChatGPT 3.5 ( p < 0.001). (4) Conclusions: The findings underscore the increased accuracy and dependability of ChatGPT 4 in the context of medical education and potential clinical decision making. Nonetheless, the research emphasizes the indispensable nature of human-delivered healthcare and the vital role of continuous assessment in leveraging AI in medicine.

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