Login / Signup

Using Machine Learning to Identify Metabolomic Signatures of Pediatric Chronic Kidney Disease Etiology.

Arthur M LeeJian HuYunwen XuAlison G AbrahamRui XiaoJosef CoreshCasey RebholzJingsha ChenEugene P RheeHarold I FeldmanVasan S RamachandranPaul L KimmelBradley A WaradySusan L FurthMichelle R Denburgnull null
Published in: Journal of the American Society of Nephrology : JASN (2022)
ML models identified metabolomic signatures based on CKD cause. Using ML techniques in conjunction with traditional biostatistics, we demonstrated that sphingomyelin-ceramide and plasmalogen dysmetabolism are associated with FSGS and that gut microbiome-derived histidine metabolites are associated with OU.
Keyphrases
  • chronic kidney disease
  • end stage renal disease
  • genome wide
  • ms ms