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DrAgnes -- Dermatology Intelligence Platform
AI-powered dermoscopy analysis with collective learning, built on the RuVector embedding engine and pi.ruv.io brain network.
Quick Start
cd examples/dragnes
npm install
npm run dev
The app starts at http://localhost:5173.
Architecture
DrAgnes is a standalone SvelteKit application that provides:
- On-device CNN inference via MobileNetV3-Small (WASM) for dermoscopy image classification across 7 HAM10000 lesion classes (akiec, bcc, bkl, df, mel, nv, vasc).
- ABCDE scoring with asymmetry, border, color, diameter, and evolution metrics.
- Grad-CAM attention overlays showing which regions influenced the classification.
- HAM10000 demographic adjustment using Bayesian priors from clinical data (age, sex, body location).
- Privacy-first design with differential privacy (epsilon=1.0), EXIF stripping, and local-only processing by default.
- Brain sync via pi.ruv.io for federated learning and collective case sharing (opt-in).
- Offline PWA with service worker caching for model weights and static assets.
Directory Structure
src/
lib/
dragnes/ # Core library: classifier, types, preprocessing, privacy
components/ # Svelte UI components: capture, results, charts, panel
routes/
+page.svelte # Main page (loads DrAgnesPanel)
api/ # Server endpoints: health, analyze, feedback, similar
static/ # PWA manifest, icons, service worker
tests/ # Unit and benchmark tests
scripts/ # Deployment and analysis scripts
docs/ # Research documentation
API Endpoints
| Method | Path | Description |
|---|---|---|
| GET | /api/health |
Health check with model info |
| POST | /api/analyze |
Classify an image embedding |
| POST | /api/feedback |
Submit clinician feedback |
| GET | /api/similar/[id] |
Find similar cases |
Testing
npm run test
Deployment
# Build for production
npm run build
# Deploy to Cloud Run
npm run deploy
See cloud-run.yaml for the Cloud Run service configuration and Dockerfile
for the container build.