v0.2.0 - `NND`

Release Date: 2025-06-02

We’re excited to announce the first release of the Neurodegenerative Disease Detector! This early version lays the foundation for detecting signs of neurodegenerative diseases using machine learning on MRI scan data.

🧠 Features

• ✅ Preprocessing pipeline for structural MRI images using nibabel and sklearn.
• ✅ Model training with a RandomForestClassifier for initial disease classification.
• ✅ Feature extraction from brain scans including volumetric data and voxel intensities.
• ✅ Training and testing split with metrics such as accuracy, precision, recall, and confusion matrix output.
• ✅ Visualization of performance metrics via matplotlib.

🛠️ Tech Stack

• Python 3.x
• Libraries: nibabel, scikit-learn, numpy, matplotlib, joblib

📁 Project Structure

• src/: Preprocessing and modeling scripts.
• data/: Example MRI datasets.
• models/: Serialized trained models (via joblib).
• notebooks/: Exploratory analysis and development logs.

⚠️ Limitations

• Only supports binary classification (e.g., Alzheimer’s vs. Healthy).
• No GUI or API for inference (CLI and Jupyter only).
• Dataset and labels are assumed to follow a specific structure.

📌 Next Steps

• Add support for multi-class classification.
• Improve preprocessing robustness and error handling.
• Deploy model via a web API or simple app interface.
• Integrate with larger open datasets like ADNI.

What's Changed

• Develop by @rorro6787 in #1

New Contributors

• @rorro6787 made their first contribution in #1

Full Changelog: v0.1.1...v0.2.0