September 5, 2025CancersOpen Access

Explainable Deep Ensemble Meta-Learning Framework for Brain Tumor Classification Using MRI Images

View Full Paper

Ask AI

Bookmark

Authors

Discussion

Demonstrates 99.83% accuracy in classifying brain tumors in MRI scans, highlighting the potential of explainable AI methods.

Achieving a classification accuracy of 99.83% demonstrates the effectiveness of the ensemble model in detecting brain tumors.
Significant improvements in generalization were noted through regularization techniques like dropout and data augmentation.
Utilizing explainable AI methods like Grad-CAM++, LIME, and SHAP helps visualize model predictions and enhances clinical trust.
The approach's robustness is supported by a comprehensive hyperparameter tuning process implemented via Optuna.

Kakon et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark