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Differences between kidney retransplant recipients as identified by machine learning consensus clustering.

Charat ThongprayoonPradeep VaitlaCaroline C JadlowiecShennen A MaoMichael A MaoPrakrati C AcharyaNapat LeeaphornWisit KaewputPattharawin PattharanitimaSupawit TangpanithandeePajaree KrisanapanPitchaphon NissaisorakarnMatthew CooperWisit Cheungpasitporn
Published in: Clinical transplantation (2023)
The use of an unsupervised machine learning approach characterized kidney retransplant recipients into three clinically distinct clusters with differing posttransplant outcomes. Recipients with moderate allosensitization, such as those represented in cluster 3, are perhaps more disadvantaged in the kidney retransplantation process. Potential opportunities for improvement specific to these re-transplant recipients include working to improve opportunities to improve access to living donor kidney transplantation, living donor paired exchange and identifying strategies for better HLA matching.
Keyphrases
  • kidney transplantation
  • machine learning
  • artificial intelligence
  • big data
  • deep learning
  • clinical practice
  • metabolic syndrome
  • adipose tissue
  • climate change