metabric-survival MelihOrel · COMPLETED
🧬 An explainable machine learning pipeline predicting 5-year breast cancer survival using the METABRIC genomic dataset. It leverages XGBoost, ADASYN for medical data imbalance, and SHAP (Explainable AI) to translate complex RNA and clinical features into transparent, biologically interpretable predictions. 🏥📊
github.com/MelihOrel/metabric-survival · ★ 2 · Forks 0 · Size 513 KB
SUMMARY
Technologies 5
Scored 5
Observed 5
Practices 6
Evidence 6
Skips 0
COVERAGE
Analyzed 12 files · 2 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
5 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 66
3 files · PRODUCTION
pandas LIBRARY Depth 66
3 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-06-17
Last commit 2026-06-17
Active months 1
Commits 2