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Open Access

Peer-reviewed

Research Article

From data to diagnosis: An innovative approach to epilepsy prediction with CGTNet incorporating spatio-temporal features

Dianli Wang,

Roles Conceptualization, Methodology, Writing – review & editing

Affiliation Changchun Sci-Tech University, Changchun, China
⨯
Enping Li,

Roles Validation, Writing – original draft

Affiliation School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun, China
⨯
Yang Wang,

Roles Software, Validation

Affiliation School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun, China
⨯
Zhiyang Liu ,

Roles Formal analysis

* E-mail: wangdianli20240111@126.com

Affiliation Changchun Sci-Tech University, Changchun, China

https://orcid.org/0009-0001-7046-5028

⨯
Aixia Sun,

Roles Investigation

Affiliation Shanghai Zhengyuan Computer Technology Co., Ltd, Shanghai, China
⨯
Wei Wei,

Roles Data curation

Affiliation Changchun Industrial Senior Technical School, Changchun, China
⨯
Xuning Zhang,

Roles Investigation

Affiliation Changchun Sci-Tech University, Changchun, China
⨯
Cheng Peng,

Roles Project administration

Affiliation Changchun Sci-Tech University, Changchun, China
⨯
Fengtao Wei

Roles Formal analysis

Affiliation Changchun Sci-Tech University, Changchun, China
⨯

From data to diagnosis: An innovative approach to epilepsy prediction with CGTNet incorporating spatio-temporal features

Dianli Wang,
Enping Li,
Yang Wang,
Zhiyang Liu,
Aixia Sun,
Wei Wei,
Xuning Zhang,
Cheng Peng,
Fengtao Wei

x

Published: December 2, 2025
https://doi.org/10.1371/journal.pone.0337007

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Electroencephalography
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Epilepsy
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Epileptic seizures
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Preprocessing
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Statistical data
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Deep learning
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Neural networks
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Machine learning
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