cvd-expert jvcByte · PARTIAL
An advanced machine learning application that predicts heart disease risk using XGBoost. Built with Streamlit and trained on over 300,000 US health records, achieving 91.5% prediction accuracy.
github.com/jvcByte/cvd-expert · ★ 0 · Forks 1 · Size 167 KB
SUMMARY
Technologies 6
Scored 5
Observed 5
Practices 6
Evidence 7
Skips 1
COVERAGE
Analyzed 9 files · 7 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
JSON LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
1 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth —
0 files · config only
pandas LIBRARY Depth 54
1 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-01-20
Last commit 2025-07-28
Active months 2
Commits 7