Brain Tumor Detection and Classification Using Deep Neural Network and Interpretation Using XAI Techniques

Clinical decision-making relies heavily on accurate brain tumor diagnosis from MRI imaging. Manual interpretation is time-consuming and error-prone. To enhance efficiency, automated techniques using deep neural networks (DNNs), particularly Convolution Neural Networks (CNNs), are proposed. This study incorporates explainable artificial intelligence (XAI) for interpretability. By addressing the need for automated and accurate diagnosis, this research aims to improve patient care and treatment outcomes, providing medical professionals with a dependable tool for brain tumor identification in clinical practice.