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This study explores the clinical context of brain tumours and the necessity for rapid, automated MRI diagnosis using various sequences like T1 and FLAIR. It reviews prior automated methods, highlighting CNN and transfer-learning approaches with accuracy rates between 90.00% and 99.40%, while noting challenges such as computational costs and biases. The key takeaway emphasizes the development of efficient Computer-Aided Diagnosis (CAD) tools that utilize balanced metrics, provide explainable...