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Obstruction risk from common ultrasound parameters in pediatric hydronephrosis with machine learning.

Adree KhondkerJethro C C KwongMargarita ChancyNeeta D'SouzaKellie KimJin K KimLai Nam TseMichael ChuaPriyank YadavLauren ErdmanJohn WeaverArmando J LorenzoMandy Rickard
Published in: BJU international (2023)
Coupled with machine learning, routine ultrasound findings can improve the criteria to determine in which children with isolated hydronephrosis a diuretic renogram can be safely avoided. Further optimization and validation are required prior to implementation into clinical practice.
Keyphrases
  • machine learning
  • clinical practice
  • magnetic resonance imaging
  • artificial intelligence
  • big data
  • primary care
  • young adults
  • healthcare
  • contrast enhanced ultrasound
  • deep learning
  • computed tomography