EEG-based schizophrenia diagnosis using deep learning with multi-scale and adaptive feature selection
Schizophrenia is a chronic and severe mental illness that significantly impacts the daily lives and work of those affected. Unfortunately, schizophrenia with negative symptoms often gets misdiagnosed, relying heavily on the clinician’s experience. There is a pressing need to develop an objective and...
Saved in:
| Main Authors: | Alanoud Al Mazroa, Majdy M. Eltahir, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K, Jaehyuk Cho |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2025-05-01
|
| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-2811.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EEG-SymNet: multi-channel EEG signal-based schizophrenia diagnosis using channel recalibration and symmetric spatial temporal transformer network
by: Naif Alsharabi, et al.
Published: (2025-09-01) -
An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms
by: Ahmad Almadhor, et al.
Published: (2025-07-01) -
An open-access EEG dataset from indigenous African populations for schizophrenia researchZenodo
by: S.K. Mosaku, et al.
Published: (2025-10-01) -
EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia
by: Shihai Ling, et al.
Published: (2025-03-01) -
3L-YOLO: A Lightweight Low-Light Object Detection Algorithm
by: Zhenqi Han, et al.
Published: (2024-12-01)