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A Random Forest Algorithm for Assessing Risk Factors Associated With Chronic Kidney Disease: Observational Study.

Pei LiuYijun LiuHao LiuLinping XiongChanglin MeiLei Yuan
Published in: Asian/Pacific Island nursing journal (2024)
Our findings reveal that the RF algorithm has significant predictive value for assessing risk factors associated with CKD and allows the screening of individuals with risk factors. This has crucial implications for early intervention and prevention of CKD.
Keyphrases
  • chronic kidney disease
  • end stage renal disease
  • risk factors
  • machine learning
  • deep learning
  • neural network
  • randomized controlled trial
  • climate change
  • genome wide
  • single cell
  • dna methylation