Your browser doesn't support javascript.
loading
[Prediction of blood tacrolimus concentration in liver transplantation recipients by artificial neural network].
Fu, Xiao-Hua; Ye, Yi-Fang; Luo, Mei-Juan; Hong, Xiao-Dan; Chen, Xiao-Lu; Yao, Qiu-Yan; Rong, Ying-Ci; Ren, Bin.
Afiliação
  • Fu XH; Guangzhou Xinhai Hospital, Guangzhou 510300, China.
Yao Xue Xue Bao ; 47(9): 1134-40, 2012 Sep.
Article em Zh | MEDLINE | ID: mdl-23227541
ABSTRACT
This study is to establish an artificial neural network (ANN) for predicting blood tacrolimus concentration in liver transplantation recipients. Tacrolimus concentration samples (176 samples) from 37 Chinese liver transplantation recipients were collected. ANN established after network parameters were optimized by using momentum method combined with genetic algorithm. Furthermore, the performance of ANN was compared with that of multiple linear regression (MLR). When using accumulated dose of 4 days before therapeutic drug monitoring (TDM) of tacrolimus concentration as input factor, mean prediction error and mean absolute prediction error of ANN were 0.02 +/- 2.40 ng x mL(-1) and 1.93 +/- 1.37 ng x mL(-1), respectively. The absolute prediction error of 84.6% of testing data sets was less than 3.0 ng x mL(-1). Accuracy and precision of ANN are superior to those of MLR. The correlation, accuracy and precision of ANN are good enough to predict blood tacrolimus concentration.
Assuntos
Buscar no Google
Base de dados: MEDLINE Assunto principal: Transplante de Fígado / Redes Neurais de Computação / Tacrolimo / Monitoramento de Medicamentos / Imunossupressores Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: Zh Ano de publicação: 2012 Tipo de documento: Article
Buscar no Google
Base de dados: MEDLINE Assunto principal: Transplante de Fígado / Redes Neurais de Computação / Tacrolimo / Monitoramento de Medicamentos / Imunossupressores Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: Zh Ano de publicação: 2012 Tipo de documento: Article