Nonlinear Feature Modeling Using Kolmogorov-Arnold Networks in Electroencephalography for Depression Classification: Deep Learning Study

Bin Yang, Yongfeng Fan, Xinhong Wei, Chunlei Shi

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DOI: 10.2196/101076
Published: 2026-10-19
Container: JMIR AI
Publisher: JMIR Publications Inc.
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.2196/101076,
  title = {Nonlinear Feature Modeling Using Kolmogorov-Arnold Networks in Electroencephalography for Depression Classification: Deep Learning Study},
  author = {Bin Yang and Yongfeng Fan and Xinhong Wei and Chunlei Shi},
  year = {2026},
  journal = {JMIR AI},
  doi = {10.2196/101076},
  url = {https://doi.org/10.2196/101076}
}

RIS

TY  - JOUR
TI  - Nonlinear Feature Modeling Using Kolmogorov-Arnold Networks in Electroencephalography for Depression Classification: Deep Learning Study
AU  - Bin Yang
AU  - Yongfeng Fan
AU  - Xinhong Wei
AU  - Chunlei Shi
PY  - 2026
JO  - JMIR AI
DO  - 10.2196/101076
UR  - https://doi.org/10.2196/101076
ER  -

APA

Yang, B., Fan, Y., Wei, X., & Shi, C. (2026). Nonlinear Feature Modeling Using Kolmogorov-Arnold Networks in Electroencephalography for Depression Classification: Deep Learning Study. JMIR AI. https://doi.org/10.2196/101076

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crossref · retrieved 2026-11-10T06:28:28.292Z