Use of Artificial Intelligence in Vesicoureteral Reflux Disease: A Comparative Study of Guideline Compliance

<b>Objective:</b> This study aimed to evaluate the compliance of four different artificial intelligence applications (ChatGPT-4.0, Bing AI, Google Bard, and Perplexity) with the American Urological Association (AUA) vesicoureteral reflux (VUR) management guidelines. <b>Materials and Methods:</b> Fifty-one questions derived from the AUA guidelines were asked of each AI application. Two experienced paediatric surgeons independently scored the responses using a five-point Likert scale. Inter-rater agreement was analysed using the intraclass correlation coefficient (ICC). <b>Results:</b> ChatGPT-4.0, Bing AI, Google Bard, and Perplexity received mean scores of 4.91, 4.85, 4.75 and 4.70 respectively. There was no statistically significant difference between the accuracy of the AI applications (<i>p</i> = 0.223). The inter-rater ICC values were above 0.9 for all platforms, indicating a high level of consistency in scoring. <b>Conclusions:</b> The evaluated AI applications agreed highly with the AUA VUR management guidelines. These results suggest that AI applications may be a potential tool for providing guideline-based recommendations in paediatric urology.

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Publication Details

Journal
Journal of Clinical Medicine
Published
2025-03-30
DOI
https://doi.org/10.3390/jcm14072378
Citations
3
Primary Topic
Pediatric Urology and Nephrology Studies
Type
article
Field-Weighted Citation Impact
10.48
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article

Use of Artificial Intelligence in Vesicoureteral Reflux Disease: A Comparative Study of Guideline Compliance

İlhan Çiftçi, Mehmet Sarıkaya, Fatma Özcan Sıkı
3 citations
Journal of Clinical Medicine
Pediatric Urology and Nephrology Studies
10.48
article

Use of Artificial Intelligence in Vesicoureteral Reflux Disease: A Comparative Study of Guideline Compliance

İlhan Çiftçi, Mehmet Sarıkaya, Fatma Özcan Sıkı
article en
3 citations

Abstract

<b>Objective:</b> This study aimed to evaluate the compliance of four different artificial intelligence applications (ChatGPT-4.0, Bing AI, Google Bard, and Perplexity) with the American Urological Association (AUA) vesicoureteral reflux (VUR) management guidelines. <b>Materials and Methods:</b> Fifty-one questions derived from the AUA guidelines were asked of each AI application. Two experienced paediatric surgeons independently scored the responses using a five-point Likert scale. Inter-rater agreement was analysed using the intraclass correlation coefficient (ICC). <b>Results:</b> ChatGPT-4.0, Bing AI, Google Bard, and Perplexity received mean scores of 4.91, 4.85, 4.75 and 4.70 respectively. There was no statistically significant difference between the accuracy of the AI applications (<i>p</i> = 0.223). The inter-rater ICC values were above 0.9 for all platforms, indicating a high level of consistency in scoring. <b>Conclusions:</b> The evaluated AI applications agreed highly with the AUA VUR management guidelines. These results suggest that AI applications may be a potential tool for providing guideline-based recommendations in paediatric urology.

Journal of Clinical MedicineVol. 14(7)
Selçuk University (TR)
Partnerships for the goals
Openalex Percentile: Top 3%
Pediatric Urology and Nephrology Studies
10.48
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Use of Artificial Intelligence in Vesicoureteral Reflux Disease: A Comparative Study of Guideline Compliance — İlhan Çiftçi, Mehmet Sarıkaya, et al. · Journal of Clinical Medicine (2025) | TGRS Research Map | TGRS