Layer-Wise Relevance Propagation Approach for Diagnosis of Drug-Naive Men With Major Depressive Disorder Using Resting-State Electroencephalography.

ABSTRACT: The advancement of artificial intelligence (AI) tools utilizing electroencephalography (EEG) for diagnosing major depressive disorder (MDD) has shown significant progress. However, the practical implementation of these tools is often impeded by the large amount of EEG data required for training AI models and the lack of explanations for the MDD diagnoses. This study aims to develop an interpretable deep-learning-based computer-aided diagnostic system for diagnosing male MDD patients using explainable AI (XAI) algorithms. The CAD system was designed to facilitate the diagnostic process by using a reduced number of EEG channels and data length while enhancing understanding of the neurophysiological characteristics of male MDD. Resting-state EEG data were collected from 40 male MDD patients (

SUBMITTER: Yi EG 

PROVIDER: S-EPMC12483754 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature