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 validated by 20-fold cross-validation. Results The true positive rate of schizophrenia prediction using the convolutional 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. Key words: Schizophrenia; Convolutional neural network; Electroencephalogram; Diagnosis
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Chinese Journal of Behavioral Medicine and Brain Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
