ReviewCanadian Urological Association journal = Journal de l'Association des urologues du Canada2026
Reporting of race and ethnicity in studies of artificial intelligence in pediatric urology A secondary analysis of the AI-PEDURO online repository.
Review in Canadian Urological Association journal = Journal de l'Association des urologues du Canada, 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
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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.
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Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionWhile an increasing number of artificial intelligence (AI) models are being developed in pediatric urology, the extent of race/ethnicity reporting among these studies is unclear. Our objective was to evaluate the inclusion and quality of race/ethnicity reporting in AI models in pediatric urology.
methodsWe conducted a secondary analysis of studies included in the AI in PEDiatric UROlogy (AI-PEDURO) collaborative living scoping review and repository. We examined racial/ethnic groups reported, their proportional representation, use of race/ethnicity as a predictor, conducting of stratified analyses by race/ethnicity, data collection methods, bias evaluation, and discussions of implications on equity.
resultsOf 81 studies in the AI-PEDURO repository, six (7.4%) reported race/ethnicity. Five studies included White and Black patients, representing 4824/7968 (60.5%) and 1377/7968 (17.3%) of the pooled cohort, respectively. Asian patients were included in three studies and represented 178/6861 (2.6%). Two studies reported Native Hawaiian or other Pacific Islander and Hispanic or Latino patients, representing 20/6704 (0.3%) and 1236/6704 (18.4%), respectively. One study included American Indian or Alaska Native patients, representing 69/6604 (1.0%). Mixed patients were included in three studies and represented 103/7711 (1.3%). Race/ethnicity was a predictor variable in 4/6 studies. None of these six studies conducted stratified analyses of model performance across race/ethnicity subgroups, reported race/ethnicity data collection methodologies, examined algorithmic biases, discussed implications on equity, or examined socioeconomic status or geographic residence.
conclusionsRace/ethnicity reporting is poor in most AI studies in pediatric urology. Standardized reporting may help ensure fairness and generalizability of models across diverse pediatric urology populations.
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.