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Brain tumor detection is a critical task in medical diagnosis, where early and accurate identification can significantly improve patient outcomes. Deep learning, a subset of artificial intelligence, has emerged as a powerful tool in automating this process. By leveraging convolutional neural networks (CNNs) and other advanced architectures, deep learning models can analyze MRI scans to detect and classify brain tumors with high accuracy. These models learn complex patterns and features from vast datasets, reducing the need for manual intervention and minimizing human error. The integration of deep learning in medical imaging enhances diagnostic speed, consistency, and precision, offering promising support for radiologists and healthcare professionals.