
Artificial Intelligence in Paediatric Urology: Transforming Diagnosis and Treatment
Correspondence Address :
Dr. Wesam Khan,
Assistant Professor, Department of Surgery, Faculty of Medicine, University of Tabuk, Tabuk, Saudi Arabia.
E-mail: Wkhan@ut.edu.sa
Artificial Intelligence (AI) is revolutionising healthcare, including paediatric urology. Paediatric urology has played a crucial role in the development of clinically relevant AI models. This narrative review explores the applications, benefits and challenges of AI in paediatric urological diagnosis and treatment. It aims to determine the current state of AI in paediatric urology, identify key applications, evaluate their impact on clinical outcomes and explore potential future directions. The literature search was extensively conducted using the PubMed, Scopus and Web of Science databases. The findings from the literature search indicate that AI has the potential to significantly improve paediatric urological care by providing more accurate diagnosis, optimising treatment decisions and enhancing surgical outcomes. However, challenges such as data quality, model generalisability and ethical implications must be resolved for widespread implementation.
Algorithms, Deep learning, Diagnosis, Machine learning, Predictive modelling, Robotic surgery, Treatment
DOI: 10.7860/JCDR/2025/78032.21050
Date of Submission: Jan 13, 2025
Date of Peer Review: Feb 18, 2025
Date of Acceptance: Mar 21, 2025
Date of Publishing: Jun 01, 2025
AUTHOR DECLARATION:
• Financial or Other Competing Interests: None
• Was informed consent obtained from the subjects involved in the study? NA
• For any images presented appropriate consent has been obtained from the subjects. NA
PLAGIARISM CHECKING METHODS:
• Plagiarism X-checker: Jan 14, 2025
• Manual Googling: Mar 17, 2025
• iThenticate Software: Mar 19, 2025 (15%)
ETYMOLOGY: Author Origin
EMENDATIONS: 5
- Emerging Sources Citation Index (Web of Science, thomsonreuters)
- Index Copernicus ICV 2017: 134.54
- Academic Search Complete Database
- Directory of Open Access Journals (DOAJ)
- Embase
- EBSCOhost
- Google Scholar
- HINARI Access to Research in Health Programme
- Indian Science Abstracts (ISA)
- Journal seek Database
- Popline (reproductive health literature)
- www.omnimedicalsearch.com