Identification of glomerulosclerosis using IBM Watson and shallow neural networks.

Journal: Journal of nephrology
PMID: 35041197

Abstract

BACKGROUND: Advanced stages of different renal diseases feature glomerular sclerosis at a histological level which is observed by light microscopy on tissue samples obtained by performing a kidney biopsy. Computer-aided diagnosis (CAD) systems leverage the potential of artificial intelligence (AI) in healthcare to support physicians in the diagnostic process.

Authors

  • Francesco Pesce
    D.E.T.O. University of Bari Medical School, Piazza Giulio Cesare, 11, Bari, 70124, Italy.
  • Federica Albanese
    Nephrology, Dialysis, and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy.
  • Davide Mallardi
    Nephrology, Dialysis, and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy.
  • Michele Rossini
    Department of Emergency and Organ Transplantation, Nephrology Unit University of Bari Aldo Moro, Bari, Italy.
  • Giuseppe Pasculli
    Nephrology, Dialysis, and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy.
  • Paola Suavo-Bulzis
    Nephrology, Dialysis, and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy.
  • Antonio Granata
    Nephrology and Dialysis Unit, "Cannizzaro" Hospital, 95123, Catania, Italy.
  • Antonio Brunetti
    Dipartimento di Ingegneria Elettrica e dell'Informazione, Politecnico di Bari, Bari, Italy.
  • Giacomo Donato Cascarano
    Department of Electrical and Information Engineering (DEI), Polytechnic University of Bari, Italy, Via Edoardo Orabona, 4, Bari, 70125, Italy.
  • Vitoantonio Bevilacqua
  • Loreto Gesualdo
    Department of Diagnostic Pathology, Bioimages and Public Health, Policlinic University Hospital, Bari, Italy.

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