conclusions attribution retraining improved mental health in the epileptic children in our study. it, therefore, seems to be an appropriate intervention for promoting the mental health of children. results the findings showed that the experimental group, in comparison with the control group, experienced a reduction in physical symptoms, anxiety and insomnia, social dysfunction, and depression a...

how to cite this article: najafi fard t, pourmohamadreza-tajrishi m, sajedi f, rezasoltani p, delavar kasmaei h. the effectiveness of attribution retraining on health enhancement of epileptic children. iran j child neurol. spring 2016; 10(2):53-59. abstract objective epilepsy is a chronic neurological disease. evidence has indicated that epilepsy has an impact on mental and physical health of c...

A novel approach is presented in this paper for improving the performance of neural-network classifiers in image recognition, segmentation, or coding applications, based on a retraining procedure at the user level. The procedure includes: 1) a training algorithm for adapting the network weights to the current condition; 2) a maximum a posteriori (MAP) estimation procedure for optimally selectin...

A novel approach is presented in this paper for improving the performance of neural network classifiers in image recognition, segmentation or coding applications, based on a retraining procedure at the user level. The procedure includes (a) a training algorithm for adapting the network weights to the current condition, (b) a maximum a posteriori (MAP) estimation procedure for optimally selectin...

In this article we introduce partial retraining, an algorithm to determine the relevance of the input variables of a trained neural network. We place this algorithm in the context of other approaches to relevance determination. Numerical experiments on both artificial and real-world problems show that partial retraining outperforms its competitors, which include methods based on constant substi...