ArticleRadiology. Artificial intelligence2026
US-derived Pediatric Kidney Length and Volume Percentiles by Age: A Big Data Approach.
Article in Radiology. Artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose To calculate new pediatric age-specific normative values and percentiles for kidney length and volume through the use of a natural language processing (NLP) model. Materials and Methods In this cross-sectional study, 24 664 US reports from 18 769 children (birth to 18 years) conducted between January 2012 and December 2022 at a tertiary children's hospital in the northeastern United States were analyzed with an NLP model. Anthropometric data from 12 595 children were used to evaluate the effect of sex and body measurements on kidney length and volume through age-adjusted quantile regression models. Age-related percentiles were established after calibration, using the lambda-mu-sigma (LMS) method by age (year), with detailed subcategories for children younger than 1 year. Volume percentiles by body surface area were also generated using the LMS method. Results A total of 24 664 reports from 18 769 children were included (median age, 7 years [IQR, 11 years]; 10 134 female children). Normative value analysis showed that kidney growth was more pronounced in the 1st year of life (1.8-cm increase in length and 16.9-cm
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