Advances in artificial intelligence and deep learning systems in ICU-related acute kidney injury.

Journal: Current opinion in critical care
Published Date: Dec 1, 2021

Abstract

PURPOSE OF REVIEW: Acute kidney injury (AKI) affects nearly 60% of all patients admitted to ICUs. Large volumes of clinical, monitoring and laboratory data produced in ICUs allow the application of artificial intelligence analytics. The purpose of this article is to assimilate and critically evaluate recently published literature regarding artificial intelligence applications for predicting, diagnosing and subphenotyping AKI among critically ill patients.

Authors

  • Tezcan Ozrazgat-Baslanti
    Department of Medicine, University of Florida, Gainesville, FL USA.
  • Tyler J Loftus
    Department of Surgery, University of Florida Health, Gainesville, FL. Electronic address: tyler.loftus@surgery.ufl.edu.
  • Yuanfang Ren
    Department of Medicine, University of Florida, Gainesville, FL USA.
  • Matthew M Ruppert
    Department of Medicine, University of Florida, Gainesville, Florida; Precision and Intelligent Systems in Medicine (Prisma(P)), University of Florida, Gainesville, Florida.
  • Azra Bihorac
    Department of Medicine, University of Florida, Gainesville, FL USA.

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