Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach

• Published in: Cognitive neurodynamics Vol. 15; no. 2; pp. 239 - 252
• Main Authors: Saeedi, Abdolkarim, Saeedi, Maryam, Maghsoudi, Arash, Shalbaf, Ahmad
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.04.2021; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Automation; Biochemistry; Biomedical and Life Sciences; Biomedicine; Brain; Classification; Cognitive Psychology; Computer Science; Connectivity analysis; Deep learning; Diagnosis; EEG; Electroencephalography; Fourier transforms; Fractals; Frequencies; Long short-term memory; Machine learning; Medical imaging; Memory; Mental depression; Mental disorders; Neural networks; Neurosciences; Patients; Power; Research Article; Temporal resolution; Transfer functions; Deep learning; Long short-term memory; Major depression disorder; Electroencephalography; Convolutional neural network; Effective connectivity
• ISSN: 1871-4080; 1871-4099
• DOI: 10.1007/s11571-020-09619-0

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologists in early diagnosis of mental disorders and preventing severe trauma. Major Depression Disorder (MDD) is a common and serious medical condition whose...