A CNN-Transformer Fusion Model for Proactive Detection of Schizophrenia Relapse from EEG Signals

A CNN-Transformer Fusion Model for Proactive Detection of Schizophrenia Relapse from EEG Signals

Proactively detecting schizophrenia relapse remains a critical challenge in psychiatric care, where traditional predictive models often fail to capture the complex neurophysiological and behavioral dynamics preceding recurrence. Existing methods typically rely on shallow architectures or unimodal da...

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Bibliographic Details
Main Authors: Sana Yasin, Muhammad Adeel, Umar Draz, Tariq Ali, Mohammad Hijji, Muhammad Ayaz, Ashraf M. Marei
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Bioengineering
Subjects:
unimodal data
robustness
transformer model
schizophrenia disorder
personalized relapse prevention
Online Access:https://www.mdpi.com/2306-5354/12/6/641
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