August 17, 2025

Classification of Brain Tumors Using Convolutional Neural Networks

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Deep learning model classifies brain tumors with 95.26% accuracy, suggesting efficiency over traditional biopsy methods.

The automated classification achieves an accuracy of 95.26% for brain tumors, enhancing diagnostic speed.
Multi-classification includes normal, glioma, meningioma, and pituitary tumor types, streamlining detection.
The method employs convolutional neural networks to identify tumor types from MRI scans effectively.
Utilizing large clinical datasets, this approach may significantly reduce human effort and potential errors in diagnosis.

Alkafrawi et al. (2022) studied this question.

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