External validation of a deep-learning model to predict severe acute kidney injury based on urine output changes in critically ill patients.

Abstract

Authors

• Francesca Alfieri
  Department of Applied Science and Technology, Politecnico Di Torino, C.so Duca degli Abruzzi 24, 10129, Turin, Italy.
• Andrea Ancona
  Department of Applied Science and Technology, Politecnico Di Torino, C.so Duca degli Abruzzi 24, 10129, Turin, Italy.
• Giovanni Tripepi
  Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, CNR-IFC, Nefrologia-Ospedali Riuniti, 89100, Reggio Calabria, Italy.
• Vincenzo Randazzo
  Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy. Electronic address: vincenzo.randazzo@polito.it.
• Annunziata Paviglianiti
  Department of Electronics and Telecomunications, Politecnico Di Torino, C.so Duca degli Abruzzi 24, 10129, Turin, Italy.
• Eros Pasero
  Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy. Electronic address: eros.pasero@polito.it.
• Luigi Vecchi
  S.C. Nefrologia e Dialisi, Azienda Ospedaliera Di Terni, Viale Tristano Di Joannuccio, 05100, Terni, Italy.
• Cristina Politi
  CNR-IFC, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Nefrologia-Ospedali Riuniti, 89100, Reggio Calabria, Italy.
• Valentina Cauda
  Department of Applied Science and Technology, Politecnico Di Torino, C.so Duca degli Abruzzi 24, 10129, Turin, Italy. Valentina.cauda@polito.it.
• Riccardo Maria Fagugli
  S.C. Nefrologia e Dialisi, Azienda Ospedaliera Di Perugia, Piazzale Giorgio Menghini 1, 06129, Perugia, Italy.

Keywords

External Resources