AIMC Topic: Transplant Recipients
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Using machine learning and an ensemble of methods to predict kidney transplant survival.
PloS one
Jan 9, 2019
We used an ensemble of statistical methods to build a model that predicts kidney transplant survival and identifies important predictive variables. The proposed model achieved better performance, measured by Harrell's concordance index, than the Esti...
Long-term Glomerular Filtration Rate and Kidney Disease: Improving Global Outcomes Stage Stability After Conversion to Once-Daily Tacrolimus in Kidney Transplant Recipients.
Transplantation proceedings
Jun 30, 2018
Close monitoring of estimated glomerular filtration rate (eGFR) is important for early recognition of worsening renal function to prevent further deterioration. Safe conversion from twice-daily tacrolimus (TD-Tac) to once-daily tacrolimus (OD-Tac) ha...
A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.
Scientific reports
Aug 21, 2017
Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, ...
Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients.
Scientific reports
Feb 8, 2017
Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction o...
Accept/decline decision module for the liver simulated allocation model.
Health care management science
Aug 30, 2014
Simulated allocation models (SAMs) are used to evaluate organ allocation policies. An important component of SAMs is a module that decides whether each potential recipient will accept an offered organ. The objective of this study was to develop and t...
Discover important donor-recipient risk factors and interactions in heart transplant primary graft dysfunction with machine learning.
Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2025
OBJECTIVES: Primary graft dysfunction (PGD) is an essential outcome after the heart transplant, which causes severe complications and symptoms for recipients. The in advance prediction of PGD can help the transplant physician better manage the risks ...
Comparison of Sarcopenia Assessment in Liver Transplant Recipients by Computed Tomography Freehand Region-of-Interest versus an Automated Deep Learning System.
Clinical transplantation
Jun 1, 2025
INTRODUCTION: Sarcopenia, or the loss of muscle quality and quantity, has been associated with poor clinical outcomes in liver transplantation such as infection, increased length of stay, and increased patient mortality. Abdominal computed tomography...
GraftIQ: Hybrid multi-class neural network integrating clinical insight for multi-outcome prediction in liver transplant recipients.
Nature communications
May 28, 2025
Liver transplant recipients (LTRs) are at risk of graft injury, leading to cirrhosis and reduced survival. Liver biopsy, the diagnostic gold standard, is invasive and risky. We developed a hybrid multi-class neural network (NN) model, 'GraftIQ,' inte...
Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data.
BMJ open
May 16, 2025
OBJECTIVES: In lung transplantation (LTx), a priority is assigned to each candidate on the waiting list. Our primary objective was to identify the key factors that influence the allocation of priorities in LTx using machine learning (ML) techniques t...
Effectiveness of eHealth for Medication Adherence in Renal Transplant Recipients: Systematic Review and Meta-Analysis.
Journal of medical Internet research
May 13, 2025
BACKGROUND: As the optimal treatment for end-stage renal disease, kidney transplantation has proven instrumental in enhancing patient survival and quality of life. Suboptimal medication adherence is recognized as an independent risk factor for poor p...
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