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Patient-independent hybrid generative-discriminative modeling for seizure detection in long-term scalp EEG.

Overview

Authors: Sehar Shahzad Farooq1,2, Abdul Rehman3, Jaehyeon Baik4, Sejoon Park4, Hosu Lee4,2
ORCID iDs: Abdul Rehman
  1. Department of Computer Science, Yeungnam University,Gyeongsan, 38541 Republic of Korea
  2. School of Aerospace Engineering, Gyeongsang National University, 52828 Jinju, Republic of Korea
  3. Convergence Institute of Human Data Technology, Jeonju University,Jeonju, 55069 Republic of Korea
  4. Department of Control and Robot Engineering, Gyeongsang National University,Jinju, 52828 Republic of Korea
Institutions: Yeungnam University (South Korea); Gyeongsang National University (South Korea); Jeonju University (South Korea)
Journal: Scientific reports, volume 16, issue 1, article 27318
Dates: received 2 January 2026; accepted 26 May 2026; published online 15 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41598-026-55673-9 · PMID 42297985 · PMCID PMC13530247 · OpenAlex W7164852139
Open access: gold, a free copy (OpenAlex)
Status: code on request
Categories: EEG (modality), human (organism), epilepsy (population)
Methods: Preprocessing, Spectral & time-frequency, Statistics, Machine learning, Physiology & signal measures
Keywords: CHB-MIT dataset, EEG, Hybrid deep learning, Interpretable AI, Seizure detection, Variational autoencoder, Computational biology and bioinformatics, Neurology, Neuroscience
MeSH: Electroencephalography*, Seizures*, Autoencoder, Boosting Machine Learning Algorithms, Female, Generative Artificial Intelligence, Humans, Male, Scalp (* major topic)
Topic: EEG and Brain-Computer Interfaces (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Gyeongsang National University; Ministry of Education, India
Citations: not cited yet (Europe PMC); 51 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Code

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The paper's code and data availability statement is in the Data section.

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Data

Datasets cited

Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it says that the code is available on request

Read it in the paper: doi.org/10.1038/s41598-026-55673-9.

Versions

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Version 2, 28 September 2026

  • Funding: added Gyeongsang National University; Ministry of Education, India

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 9 keywords, 9 MeSH terms, 44 references.

Cite

This paper

Farooq, S. S., Rehman, A., Baik, J., Park, S., & Lee, H. (2026). Patient-independent hybrid generative-discriminative modeling for seizure detection in long-term scalp EEG. Scientific reports, 16(1), 27318. https://doi.org/10.1038/s41598-026-55673-9

BibTeX

@article{farooq2026patient,
author = {Farooq, Sehar Shahzad and Rehman, Abdul and Baik, Jaehyeon and Park, Sejoon and Lee, Hosu},
title = {{Patient-independent hybrid generative-discriminative modeling for seizure detection in long-term scalp EEG}},
journal = {Scientific reports},
year = {2026},
month = jun,
volume = {16},
number = {1},
pages = {27318},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-55673-9},
url = {https://doi.org/10.1038/s41598-026-55673-9},
pmid = {42297985},
pmcid = {PMC13530247}
}

RIS

TY - JOUR
AU - Farooq, Sehar Shahzad
AU - Rehman, Abdul
AU - Baik, Jaehyeon
AU - Park, Sejoon
AU - Lee, Hosu
TI - Patient-independent hybrid generative-discriminative modeling for seizure detection in long-term scalp EEG
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/06/15
VL - 16
IS - 1
SP - 27318
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-55673-9
UR - https://doi.org/10.1038/s41598-026-55673-9
LA - en
ER -

CSL-JSON

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