Efficient EEG-based schizophrenia classification via a lightweight hybrid CNN-BiLSTM model.
- DOI
- 10.1016/j.pscychresns.2026.112315
- Published
- 2026 Sep 3
- Container
- Psychiatry research. Neuroimaging
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.pscychresns.2026.112315,
title = {Efficient EEG-based schizophrenia classification via a lightweight hybrid CNN-BiLSTM model.},
author = {Jangde AS and Verma GK},
year = {2026},
journal = {Psychiatry research. Neuroimaging},
doi = {10.1016/j.pscychresns.2026.112315},
url = {https://doi.org/10.1016/j.pscychresns.2026.112315}
}RIS
TY - JOUR TI - Efficient EEG-based schizophrenia classification via a lightweight hybrid CNN-BiLSTM model. AU - Jangde AS AU - Verma GK PY - 2026 JO - Psychiatry research. Neuroimaging DO - 10.1016/j.pscychresns.2026.112315 UR - https://doi.org/10.1016/j.pscychresns.2026.112315 ER -
APA
AS, J., & GK, V. (2026). Efficient EEG-based schizophrenia classification via a lightweight hybrid CNN-BiLSTM model.. Psychiatry research. Neuroimaging. https://doi.org/10.1016/j.pscychresns.2026.112315
Source records
- pubmed · retrieved 2026-09-26T01:46:57.958Z