Predicting mortality in hemodialysis patients using machine learning analysis.

Journal: Clinical kidney journal
Published Date: Aug 11, 2020

Abstract

BACKGROUND: Besides the classic logistic regression analysis, non-parametric methods based on machine learning techniques such as random forest are presently used to generate predictive models. The aim of this study was to evaluate random forest mortality prediction models in haemodialysis patients.

Authors

  • Victoria Garcia-Montemayor
    Department of Nephrology, Reina Sofia University Hospital, Cordoba, Spain.
  • Alejandro Martin-Malo
    Department of Nephrology, Reina Sofia University Hospital, Cordoba, Spain.
  • Carlo Barbieri
    Fresenius Medical Care Italia, Vaiano Cremasco, Cremona, Italy.
  • Francesco Bellocchio
    Fresenius Medical Care Italia, Vaiano Cremasco, Cremona, Italy.
  • Sagrario Soriano
    Department of Nephrology, Reina Sofia University Hospital, Cordoba, Spain.
  • Victoria Pendon-Ruiz de Mier
    Department of Nephrology, Reina Sofia University Hospital, Cordoba, Spain.
  • Ignacio R Molina
    Department of Nephrology, Reina Sofia University Hospital, Cordoba, Spain.
  • Pedro Aljama
    Department of Nephrology, Reina Sofia University Hospital, Cordoba, Spain.
  • Mariano Rodriguez
    Department of Nephrology, Reina Sofia University Hospital, Cordoba, Spain.

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