DementAI – Alzheimer's Disease Detection from Brain MRI using Deep Learning

This project aims to classify different stages of Alzheimer's disease (and non-demented cases) from brain MRI images using modern convolutional neural networks and explainability techniques.

4-class classification:

• Non-Demented
• Very Mild Demented
• Mild Demented
• Moderate Demented

Key Features

• State-of-the-art model: EfficientNet-B3 (pre-trained)
• Strong data augmentation & training pipeline
• Grad-CAM visualization for model interpretability (shows which brain regions the model focuses on)
• Simple Streamlit web interface for uploading and testing images
• Clean training script with validation & model checkpointing

Sample Visual Results

Brain MRI comparison – Healthy vs. Alzheimer's (noticeable atrophy in advanced cases):

Grad-CAM examples – Highlighting regions the model pays attention to:

Quick Start

# 1. Clone the repository
git clone https://github.com/Tamaris-coder/DementAI.git
cd DementAI

# 2. Install dependencies
pip install -r requirements.txt

# 3. (Optional) Train the model yourself
python train.py

# 4. Run the demo app
streamlit run app.py