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Explainable Deep Ensemble Meta-Learning Framework for Brain Tumor Classification

Deep nets learn to see—
Tumors revealed, explained clear,
Trust through transparency.
Deep learning
Brain tumor
Medical imaging
XAI
Ensemble learning

Kakon, S. Chakrabarty, Z. Al Sazid, I. A. Begum, M. A. Samad, A. S. M. S. Hosen, “Explainable Deep Ensemble Meta-Learning Framework for Brain Tumor Classification,” Cancers 17(17):2853 (2025), doi: 10.3390/cancers17172853

Authors

Kakon

S. Chakrabarty

Z. Al Sazid

I. A. Begum

Md Abdus Samad

A. S. M. S. Hosen

Published

January 2025

Doi

10.3390/cancers17172853

Abstract

Brain tumor classification from medical images is critical for diagnosis and treatment planning. This study proposes an explainable deep ensemble meta-learning framework that combines multiple deep learning models with meta-learning strategies to achieve high classification accuracy while maintaining interpretability. The framework incorporates explainable AI techniques to provide clinicians with transparent decision-making insights, enhancing trust and clinical applicability.

Citation

 Add to Zotero 

@article{KakonEtAl:2025,
  Author  = {Kakon and Chakrabarty, S. and Al Sazid, Z. and Begum, I. A. and Samad, M. A. and Hosen, A. S. M. S.},
  Title   = {Explainable Deep Ensemble Meta-Learning Framework for Brain Tumor Classification},
  Journal = {Cancers},
  Volume  = {17},
  Number  = {17},
  Pages   = {2853},
  Year    = {2025},
  Doi     = {10.3390/cancers17172853}
}