Predicting the function of transplanted kidney in long-term care processes: Application of a hybrid model
暂无分享,去创建一个
[1] Rob J. Hyndman,et al. A note on the validity of cross-validation for evaluating autoregressive time series prediction , 2018, Comput. Stat. Data Anal..
[2] Shaomin Li,et al. Improving precision of glomerular filtration rate estimating model by ensemble learning , 2017, Journal of Translational Medicine.
[3] T. Greene,et al. From Static to Dynamic Risk Prediction: Time Is Everything. , 2017, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[4] D. Kent,et al. A Dynamic Predictive Model for Progression of CKD. , 2017, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[5] Liang Li,et al. Dynamic Prediction of Renal Failure Using Longitudinal Biomarkers in a Cohort Study of Chronic Kidney Disease , 2016, Statistics in Biosciences.
[6] Graeme L. Hickey,et al. Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues , 2016, BMC Medical Research Methodology.
[7] A. Kirk,et al. Biomarkers for kidney transplant rejection , 2014, Nature Reviews Nephrology.
[8] A. Cherukuri,et al. Predicting 5-year risk of kidney transplant failure: a prediction instrument using data available at 1 year posttransplantation. , 2014, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[9] S. Hansun. A new approach of moving average method in time series analysis , 2013, 2013 Conference on New Media Studies (CoNMedia).
[10] M. Rezaei,et al. Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival , 2013 .
[11] Christophe Ley,et al. Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median , 2013 .
[12] A. Zapf,et al. Development and validation of a new statistical model for prognosis of long-term graft function after pediatric kidney transplantation , 2013, Pediatric Nephrology.
[13] Dimitris Rizopoulos,et al. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R , 2012 .
[14] Martin Vingron,et al. Predicting the outcome of renal transplantation , 2012, J. Am. Medical Informatics Assoc..
[15] Atholl Johnston,et al. Development and evaluation of a composite risk score to predict kidney transplant failure. , 2011, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[16] N. Tangri,et al. A predictive model for progression of chronic kidney disease to kidney failure. , 2011, JAMA.
[17] J. Daurès,et al. A clinical scoring system highly predictive of long-term kidney graft survival. , 2010, Kidney international.
[18] A. Goldfarb-Rumyantzev. Personalized medicine and prediction of outcome in kidney transplant. , 2010, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[19] A. Israni,et al. A simple tool to predict outcomes after kidney transplant. , 2010, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[20] Dharmendra Sharma,et al. Comparison of Artificial Neural Networks with Logistic Regression in Prediction of Kidney Transplant Outcomes , 2009, 2009 International Conference on Future Computer and Communication.
[21] M W Kattan,et al. Nomograms for predicting graft function and survival in living donor kidney transplantation based on the UNOS Registry. , 2009, The Journal of urology.
[22] John F. Hurdle,et al. Single and multiple time-point prediction models in kidney transplant outcomes , 2008, J. Biomed. Informatics.
[23] M. Salvadori,et al. Estimated One-Year Glomerular Filtration Rate is the Best Predictor of Long-term Graft Function Following Renal Transplant , 2006, Transplantation.
[24] Farid E Ahmed,et al. Molecular Cancer BioMed Central Review , 2005 .
[25] A. Zwinderman,et al. Predicting kidney graft failure using time-dependent renal function covariates. , 2003, Journal of clinical epidemiology.
[26] Christopher P. Johnson,et al. Post-transplant renal function in the first year predicts long-term kidney transplant survival. , 2002, Kidney international.
[27] D. Sargent,et al. Comparison of artificial neural networks with other statistical approaches , 2001, Cancer.
[28] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[29] H. Akaike. Fitting autoregressive models for prediction , 1969 .
[30] Ajith,et al. Novel Ensemble Decision Support and Health Care Monitoring System , 2014 .
[31] Norman Poh,et al. Data-modelling and visualisation in chronic kidney disease (CKD): a step towards personalised medicine. , 2011, Informatics in primary care.
[32] Guoqiang Peter Zhang,et al. Time series forecasting using a hybrid ARIMA and neural network model , 2003, Neurocomputing.
[33] Douglas C. Montgomery,et al. Applied Statistics and Probability for Engineers, Third edition , 1994 .
[34] Cockcroft Dw,et al. Prediction of Creatinine Clearance from Serum Creatinine , 1976 .