Alzheimer's ML Prediction

This project develops machine learning models for predicting Alzheimer's disease onset 5 years before clinical symptoms appear, using multi-modal data including genomics, cognitive assessments, and neuroimaging.

Features

• Deep learning models trained on genomic sequences and SNP data
• Time-series analysis of cognitive assessment scores
• Convolutional neural networks for MRI image analysis
• Ensemble methods combining multiple data modalities

Installation

pip install -r requirements.txt
python setup.py install

Usage

from alzheimers_ml import AlzheimerPredictor

predictor = AlzheimerPredictor()
prediction = predictor.predict(patient_data)
print(f"Risk score: {prediction.risk_score}")

Results

Our models achieve 87% accuracy in predicting Alzheimer's onset 5 years before clinical diagnosis, with particularly strong performance when combining genomic and imaging data.

License

This project is licensed under the MIT License - see the LICENSE file for details.