Login / Signup

A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children.

Jillian K WarejkoYu YamamotoAditya BiswasMiguel A VazquezUgochukwu UgwuowoMichael SimonovIshan SaranMelissa MartinJeffrey M TestaniSherry MansourDennis G MoledinaJason H GreenbergFrancis Perry Wilson
Published in: Journal of the American Society of Nephrology : JASN (2020)
Using various machine learning algorithms, we identified and validated a time-updated prediction model of ten readily available electronic health record variables to accurately predict imminent AKI in hospitalized children.
Keyphrases
  • machine learning
  • electronic health record
  • acute kidney injury
  • young adults
  • clinical decision support
  • deep learning
  • artificial intelligence