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Predicting chronic kidney disease progression with artificial intelligence.

Mario Arturo Isaza RugetNancy YomayusaCamilo A GonzálezCatherine Alvarado HFabio A de Oro VAndrés CelyJossie MurciaAbel E González-VélezAdriana RobayoClaudia Carolina Colmenares MejíaAndrea CastilloMaría I Conde
Published in: BMC nephrology (2024)
The time-to-event model performed well in predicting the three outcomes of CKD progression at five years. This model can be useful for predicting the onset and time of occurrence of the outcomes of interest in the population with established CKD.
Keyphrases
  • chronic kidney disease
  • artificial intelligence
  • end stage renal disease
  • machine learning
  • big data
  • deep learning
  • risk assessment
  • type diabetes
  • adipose tissue
  • metabolic syndrome