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Validating a Computable Phenotype for Nephrotic Syndrome in Children and Adults Using PCORnet Data.

Andrea L OliverioDorota MarchelJonathan P TroostIsabelle AyoubSalem AlmaaniJessica GrecoCheryl L TranMichelle R DenburgMichael E MathenyChad DornSusan F MassengillHailey DesmondDebbie S GipsonLaura H Mariani
Published in: Kidney360 (2021)
This computable phenotype had good classification in identifying both children and adults with primary nephrotic syndrome utilizing only ICD-9 and ICD-10 codes, which are available across institutions in the United States. This may facilitate future screening and enrollment for research studies and enable comparative effectiveness research. Further refinements to the algorithm including use of laboratory data or addition of natural language processing may help better distinguish primary and secondary causes of nephrotic syndrome.
Keyphrases
  • machine learning
  • young adults
  • deep learning
  • electronic health record
  • big data
  • autism spectrum disorder
  • healthcare
  • data analysis