Application of convolutional neural networks in the diagnosis of schizophrenia
10. 3760/cma. j. issn. 1674-6554. 2019. 07. 009
- VernacularTitle:卷积神经网络在精神分裂症诊断中的应用研究
- Author:
Jin LIU
1
;
Yong HE
;
Jiuju WANG
;
Wenxiang QUAN
;
Ju TIAN
;
Chaonan FENG
;
Haokui YU
;
Cai NAN
;
Jun JI
Author Information
1. 北京大学第六医院转化医学科 100191
- Keywords:
Schizophrenia;
Convolutional neural network;
Electroencephalogram;
Diagnosis
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2019;28(7):622-626
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the program of convolutional neural networks for the diagnosis of schizophrenia and evaluate its effects. Methods Using the convolutional neural network,the training model was trained in the lead data of 138 normal people and 183 schizophrenic patients,and the model was valida-ted by 20-fold cross-validation. Results The true positive rate of schizophrenia prediction using the convolu-tional neural network training model was 0. 749, the false positive rate was 0. 275, and the accuracy was 0. 738. Conclusion This model can achieve a strong diagnostic ability for patients with schizophrenia. Therefore,convolutional neural network for the diagnosis of schizophrenia will become an important research direction in the future.
