Data availability
Data available on request from the authors.
References
Cakir H, Caglar U, Yildiz O, Meric A, Ayranci A, Ozgor F (2023) Evaluating the performance of ChatGPT in answering questions related to urolithiasis. Int Urol Nephrol, 1–5. https://doi.org/10.1007/s11255-023-03773-0
Barash Y, Klang E, Konen E, Sorin V (2023) ChatGPT-4 assistance in optimizing emergency department radiology referrals and imaging selection. J Am Coll Radiol. https://doi.org/10.1016/j.jacr.2023.06.009
Szczesniewski JJ, Tellez Fouz C, Ramos Alba A, Diaz Goizueta FJ, García Tello A, Llanes González L (2023) ChatGPT and most frequent urological diseases: analysing the quality of information and potential risks for patients. World J Urol, 1–5. https://doi.org/10.1007/s00345-023-04563-0
Suppadungsuk S, Thongprayoon C, Krisanapan P, Tangpanithandee S, Garcia Valencia O, Miao J, Mekrasakit P, Kashani K, Cheungpasitporn W (2023) Examining the validity of ChatGPT in identifying relevant nephrology literature: findings and implications. J Clin Med 12(17):5550
Whiles BB, Bird VG, Canales BK, DiBianco JM, Terry RS (2023) Caution! AI bot has entered the patient chat: ChatGPT has limitations in providing accurate urologic healthcare advice. Urology. https://doi.org/10.1016/j.urology.2023.07.010
Gebrael G, Sahu KK, Chigarira B, Tripathi N, Mathew Thomas V, Sayegh N, Maughan BL, Agarwal N, Swami U, Li H (2023) Enhancing triage efficiency and accuracy in emergency rooms for patients with metastatic prostate cancer: a retrospective analysis of artificial intelligence-assisted triage using ChatGPT 4.0. Cancers 15(14):3717
Sarbay İ, Berikol GB, Özturan İU (2023) Performance of emergency triage prediction of an open access natural language processing based chatbot application (ChatGPT): a preliminary, scenario-based cross-sectional study. Turk J Emerg Med 23(3):156
Coates PT (2023) Association of pretransplant coronary heart disease testing with early kidney transplant outcomes. Nature 614:214–216
Lee G, Jeong CW (2023) Unleashing the potential: artificial intelligence in urology for enhanced diagnosis, treatment, and personalized care. Investig clin urol 64(4):307–309
Isha S, Shah SZ (2023) Use of artificial intelligence for analyzing kidney stone composition: are we there yet? Mayo Clin Proc: Digit Health 1(3):352–356
Author information
Authors and Affiliations
Contributions
The author has no conflicts of interest to declare.
Corresponding author
Ethics declarations
Conflict of interest
The author has no conflict of interest to declare. There is no financial interest to report. The author did not receive support from any organization for the submitted work. I certify that the submission is original work and is not under review at any other publication.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ray, P.P. ChatGPT’s competence in addressing urolithiasis: myth or reality?. Int Urol Nephrol 56, 149–150 (2024). https://doi.org/10.1007/s11255-023-03802-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11255-023-03802-y