Assessing the utility of a natural language processing model in answering common urological questions

Abstract

ABSTRACT Background ChatGPT, an interactive natural language processing model, is becoming increasingly used for medical information gathering. The objective of this study is to investigate the appropriateness of ChatGPT's responses to common urological questions compared to the Canadian Urological Association (CUA) guideline recommendations. Methods A list of 10 urological questions were developed from the CUA guidelines and patient information materials. Each question was asked three times in ChatGPT (Version 4), totaling 30 ChatGPT‐generated responses. Responses were assessed by three reviewers using a 4‐point Likert scale (0–3) to score appropriateness with CUA guidelines as a reference. The median values and variance of answer scores were calculated to form a consensus score to determine model reliability. Results Forty percent ( n = 12/30) of ChatGPT answers were deemed appropriate. The overall mean ± standard deviation score was 1.64 ± 0.85 (between “Some correct and some incorrect” and “Correct but inadequate”). When comparing question difficulty, “Easy” questions had an overall score of 1.87 ± 1.01, compared to “Medium” questions with a score of 1.31 ± 0.47. ChatGPT generated the most appropriate responses in the domains of prostate cancer (3.00 ± 0.25), erectile dysfunction (3.00 ± 0.28), andrology (3.00 ± 0.78), and kidney cancer (3.00 ± 1.00). The average variance between responses was 0.27, demonstrating strong model reliability. Conclusion This study examined the utility of ChatGPT in answering questions based on CUA clinical guidelines. Although promising, ChatGPT underperforms in answering common urological questions despite showing high levels of repeatability.

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