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Brain disorder detection using Deep Learning Uses MRI brain scan images Detects multiple brain diseases automatically Early disease detection and diagnosis Multi-class classification system Diseases detected: Glioma tumor Pituitary tumor Meningioma tumor Alzheimer’s disease Healthy brain Uses Convolutional Neural Networks (CNN) Uses Transfer Learning techniques Models used: CNN VGG16 ResNet50 Dataset collected from Kaggle MRI datasets Combined brain tumor and Alzheimer datasets 1000 images used for training 250 images used for testing Image preprocessing and normalization Pixel values converted from 0–255 to 0–1 Feature extraction using convolution layers Pooling layers reduce computation Fully connected layers perform classification Softmax activation used for multi-clas...