Prediction of chronic kidney disease and its progression by artificial intelligence algorithms.

Journal: Journal of nephrology
Published Date: May 11, 2022

Abstract

BACKGROUND AND OBJECTIVE: Aim of nephrologists is to delay the outcome and reduce the number of patients undergoing renal failure (RF) by applying prevention protocols and accurately monitoring chronic kidney disease (CKD) patients. General practitioners and nephrologists are involved in the first and in the late stages of the disease, respectively. Early diagnosis of CKD is an important step in preventing the progression of kidney damage. Our aim was to review publications on machine learning algorithms (MLAs) that can predict early CKD and its progression.

Authors

  • Francesco Paolo Schena
    Consorzio C.A.R.S.O., Università di Bari, Strada Provinciale Casamassima Km 3, 70010 Valenzano (Bari), Italy. Electronic address: paolo.schena@uniba.it.
  • Vito Walter Anelli
    Department of Electrical and Information Engineering, Polytechnic of Bari, Bari, Italy.
  • Daniela Isabel Abbrescia
    Schena Foundation, Bari, Italy.
  • Tommaso Di Noia
    Department of Electrical and Information Engineering, Polytechnic of Bari, Bari, Italy.

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