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Application of ChatGPT as a support tool in the diagnosis and management of acute bacterial tonsillitis

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Abstract

Introduction

Artificial intelligence (AI) is transforming medicine through techniques like machine learning and deep learning. AI aids diagnosis, enhances patient care, and streamlines healthcare systems. Despite potential benefits, challenges of bias and trust must be managed. Tonsillitis is a common otolaryngological condition with economic implications. The study assesses ChatGPT’s utility in the diagnosis management of bacterial tonsillitis, highlighting its potential for patient-professional interaction.

Methods

2 methods evaluated ChatGPT 3.5 diagnostic ability for tonsillitis: patient-written cases and specialist-created cases. The scenarios involved real patients and fictional cases, assessed by 15 otolaryngologists and 5 pediatricians. Variables included diagnosis accuracy, recommendations quality, and message count.

Results

A total of 35 conversations were conducted. ChatGPT achieved accurate diagnoses in 100% of cases, with an average of 3.7 ± 1.1 chat entries for diagnosis. No significant difference existed between professional and patient scenarios (p = 0.977). Recommendations were categorized: appropriate (48.57%), incomplete (45.71%), inappropriate (5.71%), with no significant intergroup difference (p = 0.196). ChatGPT consistently advised consulting a doctor and exhibited expertise in guiding medical consultations.

Conclusion

ChatGPT demonstrates promise in providing medical insights and general advice. Its diagnostic accuracy for tonsillitis is notable, but it relies on static data and lacks individual history assessment. ChatGPT shows potential for diagnostics in simpler cases like tonsillitis, but accuracy for complex conditions needs refinement. Further research is needed for validation and broader application.

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No new data were created.

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Funding

This research has not received any form of funding.

Author information

Authors and Affiliations

  1. Otorhinolaryngology - Head and Neck Surgery Department, Complexo Hospitalario Universitario A Coruña (CHUAC), A Coruña, Galicia, 15006, Spain

    Miguel Mayo-Yáñez

  2. Department of Otorhinolaryngology, Head and Neck Surgery, Hospital San Rafael (HSR), A Coruña, Spain

    Miguel Mayo-Yáñez

  3. Otorhinolaryngology - Head and Neck Surgery Research Group, Institute of Biomedical Research of A Coruña, (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Universidade da Coruña (UDC), A Coruña, Spain

    Miguel Mayo-Yáñez & Lucía González-Torres

  4. Young-Otolaryngologists of the International Federation of Oto-Rhino-Laryngological Societies (YO-IFOS) Research Study Group, Paris, 75000 , France

    Miguel Mayo-Yáñez, Alberto Maria Saibene, Fabiana Allevi, Luigi Angelo Vaira, Antonino Maniaci, Carlos M. Chiesa-Estomba & Jerome R. Lechien

  5. Pediatrics Department, Complexo Hospitalario Universitario A Coruña (CHUAC), A Coruña, 15006, Spain

    Lucía González-Torres

  6. Health Sciences, International Center for Doctorate and Advanced Studies (EIDUDC), Universidade da Coruña (UDC), A Coruña, Galicia, 15006, Spain

    Lucía González-Torres

  7. Otolaryngology Unit, Santi Paolo e Carlo Hospital, Department of Health Sciences, Università degli Studi di Milano, Milan, Italy

    Alberto Maria Saibene

  8. Maxillofacial Surgery Unit, Santi Paolo e Carlo Hospital, Department of Health Sciences, Università degli Studi di Milano, Milan, Italy

    Fabiana Allevi

  9. Maxillofacial Surgery Unit, Santi Paolo e Carlo Hospital, Department of Health Sciences, Università degli Studi di Milano, Milan, Italy

    Luigi Angelo Vaira

  10. Faculty of Medicine and Surgery, University of Enna Kore, Enna, 94100, Italy

    Antonino Maniaci

  11. Otorhinolaryngology - Head and Neck Surgery Department, Hospital Universitario Donostia. Biodonostia Research Institute, Donostia, 20014, Spain

    Carlos M. Chiesa-Estomba

  12. Department of Otolaryngology, Polyclinique de Poitiers, Elsan Hospital, Poitiers, 86000, France

    Jerome R. Lechien

  13. Department of Otolaryngology - Head & Neck Surgery, Foch Hospital, School of Medicine, UFR Simone Veil, Universit Versailles Saint-Quentin-en-Yvelines (Paris Saclay University), Paris, 91190, France

    Jerome R. Lechien

  14. Department of Human Anatomy and Experimental Oncology, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, 7000, Belgium

    Jerome R. Lechien

  15. Department of Otolaryngology - Head & Neck Surgery, CHU Saint-Pierre (CHU de Bruxelles), Brussels, 1000, Belgium

    Jerome R. Lechien

Authors
  1. Miguel Mayo-Yáñez
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  2. Lucía González-Torres
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  3. Alberto Maria Saibene
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  4. Fabiana Allevi
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  5. Luigi Angelo Vaira
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  6. Antonino Maniaci
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  7. Carlos M. Chiesa-Estomba
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  8. Jerome R. Lechien
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Contributions

Conceptualization, MMY & LGT; methodology, MMY & LGT; formal analysis, MMY & LGT; investigation, MMY & LGT; writing?original draft preparation, MMY & LGT; writing?review and editing, JRL, CMCE, FA, AMS, LAV, AM. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Miguel Mayo-Yáñez.

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All patients received and signed an informed consent to participate in the study.

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Mayo-Yáñez, M., González-Torres, L., Saibene, A. et al. Application of ChatGPT as a support tool in the diagnosis and management of acute bacterial tonsillitis. Health Technol. (2024). https://doi.org/10.1007/s12553-024-00858-3

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