An Optimized hybrid Learning Approach for Brain Tumor Identification and Segmentation

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This framework demonstrates improved tumor classification and segmentation in MRI scans, highlighting the role of machine learning.

The method achieved enhanced segmentation accuracy in brain tumor MRI scans, validating its effectiveness.
Using magnetic resonance imaging, the framework optimized decision accuracy with a hybrid learning approach.
This hybrid learning framework integrates deep learning and machine learning for efficient tumor identification.
The findings suggest this approach could be applied in clinical settings, particularly where resources are limited.

Vinayak Dubey (2025) studied this question.

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