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ChatGPT M.D.: Is There Any Room for Generative AI in Neurology and Other Medical Areas?

20 Pages Posted: 2 Mar 2023

See all articles by Bernát Nógrádi

Bernát Nógrádi

Institute of Biophysics, Biological Research Centre

Tamás Ferenc Polgár

Institute of Biophysics, Biological Research Centre; University of Szeged

Valéria Meszlényi

Institute of Biophysics, Biological Research Centre

Zalán Kádár

Institute of Biophysics, Biological Research Centre

Péter Hertelendy

University of Szeged - Department of Neurology

Anett Csáti

University of Szeged - Department of Neurology

László Szpisjak

University of Szeged - Department of Neurology

Dóra Halmi

University of Szeged - Metabolic Diseases and Cell Signaling Research Group

Barbara Erdélyi-Furka

University of Szeged - Metabolic Diseases and Cell Signaling Research Group

Máté Tóth

University of Szeged - Internal Medicine Department

Fanny Molnár

University of Szeged - Department of Family Medicine

Dávid Tóth

University of Szeged - Department of Oncotherapy

Zsófia Bősze

University of Szeged - Internal Medicine Department

Péter Klivényi

University of Szeged - Department of Neurology

László Siklós

Institute of Biophysics, Biological Research Centre

Roland Patai

Institute of Biophysics, Biological Research Centre

More...

Abstract

Background: In recent months, ChatGPT, a general artificial intelligence, has become a cultural phenomenon in the scientific community and general audience as well. A widely increasing number of papers discussed ChatGPT as a powerful tool in scientific writing and programming but its use as a medical tool is largely overlooked. Here we show that ChatGPT can be used as a valuable and innovative augmentation in modern medicine, especially as a diagnostic tool.

Methods: We used synthetic data generated by neurological experts to represent descriptive anamneses of patients with known neurology-related diseases, then the probability for an appropriate diagnosis made by ChatGPT was measured. To give clarity to the accuracy of the AI-determined diagnosis, all cases have been cross-validated by other experts and general medical doctors as well.

Findings: We found that ChatGPT-determined diagnoses can reach the probability level of other experts, furthermore, it surpasses the probability of an appropriate diagnosis if the examiner is a general medical doctor. Our results support the efficacy of general artificial intelligence like ChatGPT as a diagnostic tool in medicine.

Interpretation: In the future, it might be a useful amendment in medical practice, especially in overwhelmed fields and/or areas requiring fast decision-making like oxiology and emergency care.

Funding: The project was financially supported by the OTKA FK_22 143326 grant from the National Research, Development, and Innovation Office of the Hungarian Government.

Declaration of Interest: The authors declare that they have no competing financial interests.

Keywords: ChatGPT, large language models, artificial intelligence, clinical diagnostic, neurology

Suggested Citation

Nógrádi, Bernát and Polgár, Tamás Ferenc and Meszlényi, Valéria and Kádár, Zalán and Hertelendy, Péter and Csáti, Anett and Szpisjak, László and Halmi, Dóra and Erdélyi-Furka, Barbara and Tóth, Máté and Molnár, Fanny and Tóth, Dávid and Bősze, Zsófia and Klivényi, Péter and Siklós, László and Patai, Roland, ChatGPT M.D.: Is There Any Room for Generative AI in Neurology and Other Medical Areas?. Available at SSRN: https://ssrn.com/abstract=4372965 or http://dx.doi.org/10.2139/ssrn.4372965

Bernát Nógrádi

Institute of Biophysics, Biological Research Centre ( email )

Tamás Ferenc Polgár

Institute of Biophysics, Biological Research Centre ( email )

University of Szeged ( email )

Valéria Meszlényi

Institute of Biophysics, Biological Research Centre ( email )

Zalán Kádár

Institute of Biophysics, Biological Research Centre ( email )

Péter Hertelendy

University of Szeged - Department of Neurology ( email )

Anett Csáti

University of Szeged - Department of Neurology ( email )

László Szpisjak

University of Szeged - Department of Neurology ( email )

Dóra Halmi

University of Szeged - Metabolic Diseases and Cell Signaling Research Group ( email )

Barbara Erdélyi-Furka

University of Szeged - Metabolic Diseases and Cell Signaling Research Group ( email )

Máté Tóth

University of Szeged - Internal Medicine Department ( email )

Fanny Molnár

University of Szeged - Department of Family Medicine ( email )

Dávid Tóth

University of Szeged - Department of Oncotherapy ( email )

Zsófia Bősze

University of Szeged - Internal Medicine Department ( email )

Péter Klivényi

University of Szeged - Department of Neurology ( email )

Szeged
Hungary

László Siklós

Institute of Biophysics, Biological Research Centre ( email )

Roland Patai (Contact Author)

Institute of Biophysics, Biological Research Centre ( email )

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