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BrainGraphNet-ViT model: a hybrid model combining vision transformers and graph convolutional networks for brain tumor diagnosis.

Overview

Authors: Wajdi Elhamzi1, Raouia Mokni2,3
ORCID iDs: Wajdi Elhamzi
  1. Department of Computer Engineering, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-kharj, Saudi Arabia
  2. Advanced Technologies for Environment and Smart Cities Unit (ATES Unit), University of Sfax, Sfax, Tunisia
  3. Computer Science Department, Higher Institute of Management of Gabes (ISGG), University of Gabes, Gabes, Tunisia
Institutions: Prince Sattam Bin Abdulaziz University (Saudi Arabia); University of Sfax (Tunisia); University of Gabès (Tunisia)
Journal: Scientific reports, volume 16, issue 1, article 16772
Dates: received 23 November 2025; accepted 27 March 2026; published online 9 April 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41598-026-46803-4 · PMID 41957132 · PMCID PMC13223212 · OpenAlex W7152438149
Open access: gold, a free copy (OpenAlex)
Status: dead link
Categories: structural MRI / diffusion (modality), human (organism), other condition (population), clinical / translational (subfield)
Methods: Statistics, Machine learning
Keywords: Brain tumor diagnosis, Graph Convolutional Networks, Vision Transformer, Graph Transformer, Transfer Learning, Cancer, Computational biology and bioinformatics, Engineering, Mathematics and computing
MeSH: Brain Neoplasms*, Image Interpretation, Computer-Assisted*, Convolutional Neural Networks, Graph Neural Networks, Humans, Magnetic Resonance Imaging, Neural Networks, Computer (* major topic)
Topic: Brain Tumor Detection and Classification (Neurology, Neuroscience), according to OpenAlex
Funding: Prince Sattam bin Abdulaziz University (PSAU/2025/01/32330)
Citations: not cited yet (Europe PMC); 39 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

No file of the authors' code could be read here: it is described below, and read at its source.

kaggle.com/dsv/2645886

License: none: the authors keep all their rights
State: the link is dead, verified on 27 September 2026
Evidence: found in the paper
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link is dead (HTTP 404)
  • 27 September 2026: the link is dead (HTTP 404)
At the source: kaggle.com/dsv/2645886

Tracing map

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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability statement

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

  • no repository, dataset or request procedure was recognized in it

Read it in the paper: doi.org/10.1038/s41598-026-46803-4.

Versions

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 9 keywords, 7 MeSH terms, 1 funder, 18 references.

Cite

This paper

Elhamzi, W., & Mokni, R. (2026). BrainGraphNet-ViT model: a hybrid model combining vision transformers and graph convolutional networks for brain tumor diagnosis. Scientific reports, 16(1), 16772. https://doi.org/10.1038/s41598-026-46803-4

BibTeX

@article{elhamzi2026braingraphnet,
author = {Elhamzi, Wajdi and Mokni, Raouia},
title = {{BrainGraphNet-ViT model: a hybrid model combining vision transformers and graph convolutional networks for brain tumor diagnosis}},
journal = {Scientific reports},
year = {2026},
month = apr,
volume = {16},
number = {1},
pages = {16772},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-46803-4},
url = {https://doi.org/10.1038/s41598-026-46803-4},
pmid = {41957132},
pmcid = {PMC13223212}
}

RIS

TY - JOUR
AU - Elhamzi, Wajdi
AU - Mokni, Raouia
TI - BrainGraphNet-ViT model: a hybrid model combining vision transformers and graph convolutional networks for brain tumor diagnosis
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/04/09
VL - 16
IS - 1
SP - 16772
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-46803-4
UR - https://doi.org/10.1038/s41598-026-46803-4
LA - en
ER -

CSL-JSON

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The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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