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ABSTRACT
Brain tumors are a serious health concern as they can have significant impacts on an individual's cognitive and physical abilities. Early detection of brain tumors is essential for successful treatment and improving patient outcomes. In this project, we propose the use of convolutional neural networks (CNNs) for brain tumor detection. CNNs are a type of deep learning algorithm that are particularly well suited for image classification tasks. By training a CNN on a large dataset of brain MRIs, we aim to develop a model that can accurately identify the presence of a brain tumor in a given MRI scan. Overall, our goal is to demonstrate the potential of CNNs for early and accurate detection of brain tumors, which has the potential to significantly improve patient outcomes and save lives.
