AINeutralarXiv – CS AI · 7h ago6/10
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End-to-End Machine Learning for Depressive State Classification via EEG and fNIRS
Researchers present a machine learning framework for detecting depression through biological signals (EEG and fNIRS) rather than traditional clinical interviews, addressing the subjectivity inherent in psychiatric diagnosis. The pilot study with eleven healthy students establishes a foundational approach for automated, objective depression screening that could be particularly valuable for identifying latent cases and differentiating depression from dementia in aging populations.