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Machine-learning models tested on bladder studies in spina bifida

A medRxiv preprint reports that three adapted machine-learning models were evaluated on videourodynamic data from an independent cohort of patients with spina bifida. A model combining pressure-volume measurements and fluoroscopic images had the strongest reported results for predicting hydronephrosis and classifying bladder dysfunction.