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To predict the risk of chronic kidney disease (CKD) using Generalized Additive2 Models (GA2M).

Francesco LapiLorenzo NutiEttore MarconiGerardo MedeaIacopo CricelliMatteo PapiMarco GoriniMatteo FioraniGaetano PiccinocchiClaudio Cricelli
Published in: Journal of the American Medical Informatics Association : JAMIA (2023)
The GA2M was reliably performant in predicting CKD in primary care. A related decision support system might be therefore implemented.
Keyphrases
  • chronic kidney disease
  • pet ct
  • primary care
  • end stage renal disease
  • general practice