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CAE-BrainNet: a statistically validated class-adaptive attention ensemble model for explainable brain tumor classification from MRI.

Overview

Authors: Mehedi Hasan Meraj1, Mashfiquzzaman Tajbid1, Mayen Uddin Mojumdar1, Narayan Ranjan Chakraborty1, Mohammaed Jabed Morshed Chowdhury1,2, Kamanashis Biswas3
ORCID iDs: Mohammaed Jabed Morshed Chowdhury
  1. Multidisciplinary Action Research (MARS) Lab, Department of Computer Science and Engineering, Daffodil International University, Birulia, Dhaka, 1216 Bangladesh
  2. Department of Computer Science and IT, La Trobe University, Melbourne, VIC Australia
  3. Peter Faber Business School, Australian Catholic University, Brisbane, QLD Australia
Institutions: Daffodil International University (Bangladesh); La Trobe University (Australia); Australian Catholic University (Australia)
Journal: Brain informatics, volume 13, issue 1, article 40
Dates: received 15 February 2026; accepted 14 July 2026; published online 26 July 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1186/s40708-026-00325-x · PMID 42678664 · PMCID PMC13534405 · OpenAlex W7171328878
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: structural MRI / diffusion (modality), other condition (population)
Methods: Machine learning, Statistics, fMRI & imaging
Keywords: Brain tumor classification, Class-adaptive ensemble, Computer-aided diagnosis (CAD), Explainable AI (XAI), Magnetic resonance imaging (MRI), Statistical validation
Topic: Brain Tumor Detection and Classification (Neurology, Neuroscience), according to OpenAlex
Funding: La Trobe University
Citations: not cited yet (Europe PMC); 63 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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Tracing map

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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/10.1186/s40708-026-00325-x.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 6 keywords, 1 funder, 24 references.

Cite

This paper

Meraj, M. H., Tajbid, M., Mojumdar, M. U., Chakraborty, N. R., Chowdhury, M. J. M., & Biswas, K. (2026). CAE-BrainNet: a statistically validated class-adaptive attention ensemble model for explainable brain tumor classification from MRI. Brain informatics, 13(1), 40. https://doi.org/10.1186/s40708-026-00325-x

BibTeX

@article{meraj2026cae,
author = {Meraj, Mehedi Hasan and Tajbid, Mashfiquzzaman and Mojumdar, Mayen Uddin and Chakraborty, Narayan Ranjan and Chowdhury, Mohammaed Jabed Morshed and Biswas, Kamanashis},
title = {{CAE-BrainNet: a statistically validated class-adaptive attention ensemble model for explainable brain tumor classification from MRI}},
journal = {Brain informatics},
year = {2026},
month = jul,
volume = {13},
number = {1},
pages = {40},
publisher = {Springer},
issn = {2198-4018},
doi = {10.1186/s40708-026-00325-x},
url = {https://doi.org/10.1186/s40708-026-00325-x},
pmid = {42678664},
pmcid = {PMC13534405}
}

RIS

TY - JOUR
AU - Meraj, Mehedi Hasan
AU - Tajbid, Mashfiquzzaman
AU - Mojumdar, Mayen Uddin
AU - Chakraborty, Narayan Ranjan
AU - Chowdhury, Mohammaed Jabed Morshed
AU - Biswas, Kamanashis
TI - CAE-BrainNet: a statistically validated class-adaptive attention ensemble model for explainable brain tumor classification from MRI
T2 - Brain informatics
J2 - Brain Inform
PY - 2026
DA - 2026/07/26
VL - 13
IS - 1
SP - 40
SN - 2198-4018
PB - Springer
DO - 10.1186/s40708-026-00325-x
UR - https://doi.org/10.1186/s40708-026-00325-x
LA - en
ER -

CSL-JSON

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"title": "CAE-BrainNet: a statistically validated class-adaptive attention ensemble model for explainable brain tumor classification from MRI",
"container-title": "Brain informatics",
"author": [
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"given": "Mehedi Hasan"
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"language": "en",
"issued": {
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}

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