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Frequently asked questions on erectile dysfunction: evaluating artificial intelligence answers with expert mentorship

Abstract

The present study assessed the accuracy of artificiaI intelligence-generated responses to frequently asked questions on erectile dysfunction. A cross-sectional analysis involved 56 erectile dysfunction-related questions searched on Google, categorized into nine sections: causes, diagnosis, treatment options, treatment complications, protective measures, relationship with other illnesses, treatment costs, treatment with herbal agents, and appointments. Responses from ChatGPT 3.5, ChatGPT 4, and BARD were evaluated by two experienced urology experts using the F1 and global quality scores (GQS) for accuracy, relevance, and comprehensibility. ChatGPT 3.5 and ChatGPT 4 achieved higher GQS than BARD in categories such as causes (4.5 ± 0.54, 4.5 ± 0.51, 3.15 ± 1.01, respectively, p < 0.001), treatment options (4.35 ± 0.6, 4.5 ± 0.43, 2.71 ± 1.38, respectively, p < 0.001), protective measures (5.0 ± 0, 5.0 ± 0, 4 ± 0.5, respectively, p = 0.013), relationships with other illnesses (4.58 ± 0.58, 4.83 ± 0.25, 3.58 ± 0.8, respectively, p = 0.006), and treatment with herbal agents (3 ± 0.61, 3.33 ± 0.83, 1.8 ± 1.09, respectively, p = 0.043). F1 scores in categories: causes (1), diagnosis (0.857), treatment options (0.726), and protective measures (1), indicated their alignment with the guidelines. There was no significant difference between ChatGPT 3.5 and ChatGPT 4 regarding answer quality, but both outperformed BARD in the GQS. These results emphasize the need to continually enhance and validate AI-generated medical information, underscoring the importance of artificiaI intelligence systems in delivering reliable information on erectile dysfunction.

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Authors and Affiliations

  1. Department of Urology, University of Gaziantep, Gaziantep, Turkey

    Muharrem Baturu & Omer Bayrak

  2. Department of Urology, Hasan Kalyoncu University, Gaziantep, Turkey

    Mehmet Solakhan

  3. Department of Biostatistics, University of Gaziantep, Gaziantep, Turkey

    Tanyeli Guneyligil Kazaz

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  1. Muharrem Baturu
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Concept – ÖB, MB; Design – ÖB, MS, MB; Supervision – ÖB, Resources – MS, MB; Materials-MB, ÖB, MS; Data Collection and/or Processing – MB, T; Analysis and/or Interpretation – TK, MB; Literature Search MS, ÖB, MB; Writing Manuscript – ÖB, MB; Critical Review – ÖB.

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Baturu, M., Solakhan, M., Kazaz, T.G. et al. Frequently asked questions on erectile dysfunction: evaluating artificial intelligence answers with expert mentorship.
Int J Impot Res (2024). https://doi.org/10.1038/s41443-024-00898-3

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  • Received: 07 August 2023

  • Revised: 28 March 2024

  • Accepted: 25 April 2024

  • Published: 07 May 2024

  • DOI: https://doi.org/10.1038/s41443-024-00898-3

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