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Analysis of clinical predictors of kidney diseases in type 2 diabetes patients based on machine learning.

Dongna HuiYiyang SunShixin XuJunjie LiuPing HeYuhui DengHuaxiong HuangXiaoshuang ZhouRongshan Li
Published in: International urology and nephrology (2022)
Predictive factors were successfully identified among different renal diseases in type 2 diabetes patients via machine learning methods. More attention should be paid on the coagulation factors in the DKD + NDKD patients, which might indicate a hypercoagulable state and an increased risk of thrombosis.
Keyphrases
  • type diabetes
  • machine learning
  • end stage renal disease
  • newly diagnosed
  • ejection fraction
  • peritoneal dialysis
  • cardiovascular disease
  • adipose tissue
  • pulmonary embolism
  • weight loss
  • big data