About This Project
A machine learning study that classifies neonates as preterm or full-term from structural brain connectivity matrices. The work tackles class imbalance and feature overlap across several classifiers, with results explored through a Streamlit interface.
Key Features
- Brain connectivity feature engineering
- Classifier benchmarking on imbalanced data
- Interactive Streamlit exploration
Technologies
Scikit-LearnMedical AIPython