Pilot study of machine learning in the task of distinguishing high and low-grade pediatric hydronephrosis on ultrasound.

Our findings demonstrate the potential of machine learning in the differentiation between low and high-grade hydronephrosis. Further studies are warranted to validate our findings and their generalizability for use in clinical practice as a means to predict clinical outcomes and the resolution of hydronephrosis.