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Distinct clinical profiles and post-transplant outcomes among kidney transplant recipients with lower education levels: uncovering patterns through machine learning clustering.

Charat ThongprayoonJing MiaoCaroline JadlowiecShennen A MaoMichael MaoNapat LeeaphornWisit KaewputPattharawin PattharanitimaOscar A Garcia ValenciaSupawit TangpanithandeePajaree KrisanapanSupawadee SuppadungsukPitchaphon NissaisorakarnMatthew CooperWisit Cheungpasitporn
Published in: Renal failure (2023)
Through unsupervised machine learning, this study proficiently categorized kidney recipients with lesser education into four distinct clusters. Notably, the standout performance of Cluster 2 provides invaluable insights, underscoring the necessity for adept risk assessment and tailored transplant strategies, potentially elevating care standards for this patient cohort.
Keyphrases
  • machine learning
  • healthcare
  • quality improvement
  • risk assessment
  • artificial intelligence
  • big data
  • palliative care
  • case report
  • deep learning
  • single cell
  • pain management
  • kidney transplantation
  • chronic pain