Predicting Kidney Graft Survival Using Machine Learning Methods: Prediction Model Development and Feature Significance Analysis Study

Comparing machine learning and regression models for mortality prediction based on the Hungarian Myocardial Infarction Registry

(2019) Péter Piros et al.   KNOWLEDGE-BASED SYSTEMS

Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study

(2019) Alexandre Loupy et al.   BMJ-British Medical Journal

Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models

(2019) Sameera Senanayake et al.   INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

An economic assessment of contemporary kidney transplant practice

(2018) David A. Axelrod et al.   AMERICAN JOURNAL OF TRANSPLANTATION

Predicting graft survival among kidney transplant recipients: A Bayesian decision support model

(2018) Kazim Topuz et al.   DECISION SUPPORT SYSTEMS

Personalized survival predictions via Trees of Predictors: An application to cardiac transplantation

(2018) Jinsung Yoon et al.   PLoS One

A dynamic model for predicting graft function in kidney recipients’ upcoming follow up visits: a clinical application of artificial neural network

(2018) Parviz Rashidi Khazaee et al.   INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

Allocation of deceased donor kidneys: A review of international practices

(2018) Darren Lee et al.   NEPHROLOGY

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

(2017) Kyung Don Yoo et al.   Scientific Reports

Prolonged warm ischemia time is associated with graft failure and mortality after kidney transplantation

(2016) Karthik K. Tennankore et al.   KIDNEY INTERNATIONAL

Applications of Deep Learning in Biomedicine

(2016) Polina Mamoshina et al.   MOLECULAR PHARMACEUTICS

Kidney Transplant Failure: Failing Kidneys, Failing Care?

(2014) J. Perl   Clinical Journal of the American Society of Nephrology

Survival analysis and regression models

(2014) Brandon George et al.   JOURNAL OF NUCLEAR CARDIOLOGY

Bayesian Modeling of Pretransplant Variables Accurately Predicts Kidney Graft Survival

(2012) Trevor S. Brown et al.   AMERICAN JOURNAL OF NEPHROLOGY

Increasing the pool of deceased donor organs for kidney transplantation

(2012) Jesse D. Schold et al.   Nature Reviews Nephrology

Who Is the High-Risk Recipient? Predicting Mortality After Heart Transplant Using Pretransplant Donor and Recipient Risk Factors

(2011) Kimberly N. Hong et al.   ANNALS OF THORACIC SURGERY

Support vector methods for survival analysis: a comparison between ranking and regression approaches

(2011) Vanya Van Belle et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Prediction of Chronic Allograft Nephropathy Using Classification Trees

(2010) D. Lofaro et al.   TRANSPLANTATION PROCEEDINGS

Nomograms for Predicting Graft Function and Survival in Living Donor Kidney Transplantation Based on the UNOS Registry

(2009) H.Y. Tiong et al.   JOURNAL OF UROLOGY

A Comprehensive Risk Quantification Score for Deceased Donor Kidneys: The Kidney Donor Risk Index

(2009) Panduranga S. Rao et al.   TRANSPLANTATION

Single and multiple time-point prediction models in kidney transplant outcomes

(2008) Ray S. Lin et al.   JOURNAL OF BIOMEDICAL INFORMATICS