Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study

2026-02-10 nephrology Title + abstract only

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Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidney failure, but predicting individual progression remains challenging. This multicenter study developed and validated POCC, a machine learning model for predicting kidney failure risk at 1, 3, and 5 years post-diagnosis in CAKUT patients. Two versions were created using data from 2,249 children. The general model achieved internal AUCs of 0.93-0.99 and external AUCs of 0.90-0.98 and 0.81- 0.90 in ...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study

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