ReviewCureus2026
Transforming Pediatric Urology With Artificial Intelligence: A Narrative Review of Current Evidence and Practice.
Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of artificial intelligence (AI) with pediatric urology is reshaping clinical care by enhancing diagnostic accuracy, surgical planning, and postoperative monitoring. AI integration offers significant advancements in managing conditions like hydronephrosis, where deep learning models automate severity grading and predict obstruction more accurately than conventional methods. In penile anomalies, such as hypospadias, AI reduces subjectivity through standardized image analysis, aiding in diagnosis and surgical decision-making. Furthermore, machine learning algorithms assist in risk-stratifying patients with vesicoureteral reflux to optimize antibiotic prophylaxis and predict resolution. Beyond diagnostics, AI enhances surgical precision in procedures like pyeloplasty through 3D simulation and real-time intraoperative navigation. However, widespread adoption is currently limited by challenges such as data scarcity, strict privacy regulations, and the need for ethical legal frameworks regarding patient data. Future developments must focus on creating transparent, interpretable decision support systems that can safely integrate into standard clinical workflows.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.