Urologists rely heavily on videourodynamics (VUDS) to identify patients with neurogenic bladders who are at risk of upper tract injury, but their interpretation has high interobserver variability. Our objective was to develop deep learning models of VUDS studies to categorize severity of bladder dysfunction.