Multiclass EEG-Based Classification of Psychiatric Disorders Using Interpretable Machine Learning on Spectral and Connectivity Features
The results suggest that EEG-derived spectral and coherence features, when combined with lightweight machine learning classifiers, can support multiclass psychiatric classification with variable class-wise performance, however, the lower performance observed for Mood Disorder and the reliance on a single public dataset...