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tests refactor(dragnes): move to standalone examples/dragnes/ app 2026-03-21 22:15:50 +00:00
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README.md

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.

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