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

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

Background. Renal replacement therapy (RRT) is a public health problem worldwide. Kidney transplantation (KT) is the best treatment for elderly patients’ longevity and quality of life. Objectives. The primary endpoint was to compare elderly versus younger KT recipients by analyzing the risk covariab...

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Main Authors: Ubiracé Fernando Elihimas Júnior, Jamila Pinho Couto, Wallace Pereira, Michel Pompeu Barros de Oliveira Sá, Eduardo Eriko Tenório de França, Filipe Carrilho Aguiar, Diogo Buarque Cordeiro Cabral, Saulo Barbosa Vasconcelos Alencar, Saulo José da Costa Feitosa, Thais Oliveira Claizoni dos Santos, Helen Conceição dos Santos Elihimas, Emilly Pereira Alves, Marcio José de Carvalho Lima, Frederico Castelo Branco Cavalcanti, Paulo Adriano Schwingel
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Journal of Aging Research
Online Access:http://dx.doi.org/10.1155/2020/7413616
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http://dx.doi.org/10.1155/2020/7413616

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