Cargando…
Classification Models to Predict Survival of Kidney Transplant Recipients Using Two Intelligent Techniques of Data Mining and Logistic Regression
Kidney transplantation is the treatment of choice for patients with end-stage renal disease (ESRD). Prediction of the transplant survival is of paramount importance. The objective of this study was to develop a model for predicting survival in kidney transplant recipients. In a cross-sectional study...
Autores principales: | Nematollahi, M., Akbari, R., Nikeghbalian, S., Salehnasab, C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Avicenna Organ Transplantation Institute
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5611541/ https://www.ncbi.nlm.nih.gov/pubmed/28959387 |
Ejemplares similares
-
Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot
por: Elihimas Júnior, Ubiracé Fernando, et al.
Publicado: (2020) -
Classification of COVID19 Patients Using Robust Logistic Regression
por: Ghosh, Abhik, et al.
Publicado: (2022) -
Predicting technique survival in peritoneal dialysis patients: comparing artificial neural networks and logistic regression
por: Tangri, Navdeep, et al.
Publicado: (2008) -
Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis
por: Harrell, Frank E
Publicado: (2001) -
Classification of Kidney Transplant Recipients Using a Combination of Estimated GFR and Albuminuria Reflects Risk
por: White, Christine A., et al.
Publicado: (2016)