Problem statement : Alzheimer's disease is the leading cause of dementia in adults aged 65 and older, characterized by irreversible neurological progression. Early detection is crucial to prevent significant brain damage. This study proposes a Deep Learning approach using MRI to identify Alzheimer's. A global Alzheimer's diagnosis occurs every four seconds, with fatal outcomes. Early identification is essential as dementia, mainly caused by Alzheimer's, impairs autonomous functioning and memory. The proposed model categorizes Alzheimer's severity (mild, moderate, or none) based on brain MRI, comparing Resnet50V2 (pretrained on the ImageNet dataset) designs to determine the most promising outcomes.

🐍 Install my-project with npm

  git clone https://github.com/Vibeflow12/DIAGNOSIS-OF-ALZHEIMER-S-USING-DEEP-LEARNING-RESNET50V2-.git
  pip install -r requirements.txt

Note : pickle file is used to show history of the model(ResNet50V2)

ADNI Dataset for kaggle : https://www.kaggle.com/datasets/lukechugh/best-alzheimer-mri-dataset-99-accuracy#