The research introduced a Brain Tumor Classification Model (BCM-CNN) to improve brain tumor diagnosis. The BCM-CNN is based on two submodules: CNN hyperparameters optimization using an adaptive dynamic sine-cosine fitness grey wolf optimizer (ADSCFGWO) algorithm and a segmentation model. The ADSCFGWO algorithm combines the strengths of the sine cosine and grey wolf algorithms. The experimental results show that the BCM-CNN achieved the best results due to the enhancement of the CNN's performance by the CNN optimization's hyperparameters
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