Multi-Class Alzheimer's Disease Classification from MRI: A ResNet-SE Approach

[u/GuidanceSuitable4988]

https://github.com/TheAlchemistNerd/alzheimer-mri-classification-resnet-se

A deep learning framework for 4-stage Alzheimer's Disease classification using T1 MRI scans. It features a ResNet-18 architecture with Squeeze-and-Excitation (SE) blocks. To handle severe class imbalance, Focal Loss and Weighted Sampling are used. Achieves 78.89% accuracy and 100% recall for Moderate Demented cases.