Research on Early Identification of Bipolar Disorder Based on Multi-layer Perceptron Neural Network.
- Author:
Haowei ZHANG
;
Yanni GAO
;
Chengmei YUAN
;
Ying LIU
;
Yuqing DING
- Publication Type:Journal Article
- MeSH:
Bipolar Disorder;
diagnosis;
Humans;
Neural Networks (Computer)
- From:
Journal of Biomedical Engineering
2015;32(3):537-541
- CountryChina
- Language:Chinese
-
Abstract:
Multi-layer perceptron (MLP) neural network belongs to multi-layer feedforward neural network, and has the ability and characteristics of high intelligence. It can realize the complex nonlinear mapping by its own learning through the network. Bipolar disorder is a serious mental illness with high recurrence rate, high self-harm rate and high suicide rate. Most of the onset of the bipolar disorder starts with depressive episode, which can be easily misdiagnosed as unipolar depression and lead to a delayed treatment so as to influence the prognosis. The early identifica- tion of bipolar disorder is of great importance for patients with bipolar disorder. Due to the fact that the process of early identification of bipolar disorder is nonlinear, we in this paper discuss the MLP neural network application in early identification of bipolar disorder. This study covered 250 cases, including 143 cases with recurrent depression and 107 cases with bipolar disorder, and clinical features were statistically analyzed between the two groups. A total of 42 variables with significant differences were screened as the input variables of the neural network. Part of the samples were randomly selected as the learning sample, and the other as the test sample. By choosing different neu- ral network structures, all results of the identification of bipolar disorder were relatively good, which showed that MLP neural network could be used in the early identification of bipolar disorder.
