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A Multimodal Deep Learning Based Framework for Early and Accurate Diagnosis of Depression Using Electroencephalography and Event‐Related Potential Signals
This is the first study to integrate EEG and ERP data in a multimodal fashion using three feature sets, achieving a high accuracy of 91% with GRU‐based classification and indicates that the combination of multimodal features and deep learning can help improve the accuracy of depression diagnosis and develop effective a...