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Transplant Recipients

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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
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...

Accept/decline decision module for the liver simulated allocation model.

Health care management science
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...

Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients.

Scientific reports
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...

A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

Scientific reports
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, ...

Using machine learning and an ensemble of methods to predict kidney transplant survival.

PloS one
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...

Prediction modeling-part 2: using machine learning strategies to improve transplantation outcomes.

Kidney international
Kidney transplant recipients and transplant physicians face important clinical questions where machine learning methods may help improve the decision-making process. This mini-review explores potential applications of machine learning methods to key ...