Login / Signup

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. This article is protected by copyright. All rights reserved.
Keyphrases
  • kidney transplantation
  • machine learning
  • artificial intelligence
  • big data
  • deep learning
  • high intensity
  • type diabetes
  • rna seq
  • single cell
  • skeletal muscle
  • metabolic syndrome
  • insulin resistance