A deep learning framework for automatic diagnosis of unipolar depression.

Journal: International journal of medical informatics
Published Date:

Abstract

BACKGROUND AND PURPOSE: In recent years, the development of machine learning (ML) frameworks for automatic diagnosis of unipolar depression has escalated to a next level of deep learning frameworks. However, this idea needs further validation. Therefore, this paper has proposed an electroencephalographic (EEG)-based deep learning framework that automatically discriminated depressed and healthy controls and provided the diagnosis.

Authors

  • Wajid Mumtaz
    Center for Intelligent Signal and Imaging Research (CISIR), Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak Malaysia.
  • Abdul Qayyum
    Department of Agronomy, The University of Haripur, Haripur 22620, Pakistan.