Impact of Feature Selection Techniques on the Performance of Machine Learning Models for Depression Detection Using EEG Data

Impact of Feature Selection Techniques on the Performance of Machine Learning Models for Depression Detection Using EEG Data

Major depressive disorder (MDD) poses a significant challenge in mental healthcare due to difficulties in accurate diagnosis and timely identification. This study explores the potential of machine learning models trained on EEG-based features for depression detection. Six models and six feature sele...

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Bibliographic Details
Main Authors: Marwa Hassan, Naima Kaabouch
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
depression detection
feature selection
machine learning
Electroencephalography (EEG)
major depressive disorder (MDD)
Online Access:https://www.mdpi.com/2076-3417/14/22/10532
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https://www.mdpi.com/2076-3417/14/22/10532

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