Depression Identification Using Asymmetry Matrix and Machine Learning Algorithms

Depression Identification Using Asymmetry Matrix and Machine Learning Algorithms

Purpose: Developing an efficient and reliable method for the identification of depression has high importance. The aim of this paper is to propose an approach for depression diagnosis using an interhemispheric asymmetry matrix and machine learning algorithms. Materials and Methods: First, EEG si...

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Bibliographic Details
Main Authors: Majid Torabi Nikjeh, Mehdi Dehghani, Vahid Asayesh, Sepideh Akhtari Khosroshahi
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2023-12-01
Series:Frontiers in Biomedical Technologies
Subjects:
Depression
Electroencephalogram
Asymmetry Matrix
Machine Learning Algorithms
Online Access:https://fbt.tums.ac.ir/index.php/fbt/article/view/553

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