metadata
title: Gallstone Risk Demo
emoji: 🩺
colorFrom: green
colorTo: gray
sdk: docker
app_port: 8000
pinned: false
license: mit
short_description: Rural adaptation of UCI Gallstone (GB + SHAP + bioimpedance)
Gallstone Risk — FastAPI backend
Rural-adaptation inference API for a gallstone disease ML case study.
Serves a scikit-learn Pipeline(StandardScaler → GradientBoostingClassifier)
trained on the UCI Gallstone dataset (319 records, 25 features — no blood lab
work), plus a SHAP TreeExplainer and a bioimpedance template generator.
- Model metrics: Accuracy 0.7708, AUC 0.8138
- Frontend: gallstone.rosewt.dev (Next.js / Vercel)
- Source: github.com/rosewt-upc/WinterProject
Endpoints
| Method | Path | Purpose |
|---|---|---|
GET |
/health |
Liveness + model/explainer load state |
GET |
/model/info |
Metrics JSON from training run |
POST |
/predict/rural |
25-feature payload → probability + risk_level |
POST |
/explain/rural |
Same payload → SHAP values + base_value |
POST |
/generate/bioimpedance |
Demographics → 15 synthetic bioimpedance vars |
Validate with the Postman collection shipped in the source repo
(demo/backend/postman_collection.json, 31 assertions).
Academic project · UPC 2024 · Does not replace medical diagnosis.