Project Launched: Interpretable AI for Early Alzheimer’s Prediction
I’ve successfully built and released an end-to-end interpretable machine learning pipeline for early Alzheimer’s risk and progression prediction using clinical data.
Key highlights:
- Robust preprocessing with imputation and scaling
- Interpretable baseline and ensemble ML models
- SHAP-based explainability for transparent predictions
- Fully reproducible Google Colab notebook
- Demo walkthrough showing real-time model outputs
This project focuses on trust, transparency, and real-world clinical relevance.
Feedback and suggestions are very welcome!
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