Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review.

Journal: Journal of nephrology
Published Date: Feb 14, 2023

Abstract

OBJECTIVES: In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the available evidence on these innovative techniques to improve CKD diagnosis and patient management.

Authors

  • Francesco Sanmarchi
    Department of Biomedical and Neuromotor Science, Alma Mater Studiorum, University of Bologna, Via San Giacomo 12, 40126, Bologna, Italy.
  • Claudio Fanconi
    Department of Electrical Engineering and Information Technology, ETH Zurich, Zurich, Switzerland.
  • Davide Golinelli
    Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
  • Davide Gori
    Department of Biomedical and Neuromotor Science, Alma Mater Studiorum, University of Bologna, Via San Giacomo 12, 40126, Bologna, Italy.
  • Tina Hernandez-Boussard
    Stanford Center for Biomedical Informatics Research, Stanford, California 94305, USA.
  • Angelo Capodici
    Department of Health Management (Direzione Sanitaria), IRCCS Istituto Ortopedico Rizzoli, Bologna, 40127, Italy.

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