This project uses a TinyVGG16-based CNN to classify MRI scans for Alzheimer's Disease stages: Mild Impairment, Moderate Impairment, No Impairment, and Very Mild Impairment. It includes Jupyter notebooks for training and prediction, and a Streamlit app for easy inference. The model achieves high metrics in predicting Alzheimer's stages.
ai deep-learning pytorch medical-imaging image-classification neuroimaging mri-images kaggle-dataset alzeheimers cnn-classification pytorch-cnn-classification ai-in-healthcare streamlit streamlit-webapp tinyvgg
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Updated
Nov 26, 2024 - Jupyter Notebook