27 lines
1.4 KiB
Markdown
27 lines
1.4 KiB
Markdown
# High-Level Targets: zhealth
|
|
|
|
## Vision
|
|
To provide a seamless, AI-powered health management platform that empowers users to track, analyze, and optimize their biomarkers for better longevity and wellness.
|
|
|
|
## Phase 1: MVP (Minimum Viable Product)
|
|
- [ ] **Unified Dashboard**: A clean UI to visualize biomarker trends (e.g., Blood Glucose, LDL, HDL, Vitamin D).
|
|
- [ ] **Rust Backend**: Secure and performant API to handle user data and biomarker logs.
|
|
- [ ] **AI Insights Prototype**: Initial integration with LLM to provide basic interpretations of biomarker results based on standard clinical ranges.
|
|
- [ ] **Data Entry**: Easy manual entry form for blood test results.
|
|
|
|
## Phase 2: Advanced AI & Integration
|
|
- [ ] **Predictive Trends**: AI models to predict future biomarker levels based on lifestyle data.
|
|
- [ ] **Lab Report OCR**: Automated data entry by uploading PDFs/images of lab reports.
|
|
- [ ] **Wearable Sync**: Integration with Apple Health, Google Fit, or Oura for holistic health context.
|
|
|
|
## Phase 3: Personalized Recommendations
|
|
- [ ] **Lifestyle Playbooks**: AI-generated nutrition and supplement plans.
|
|
- [ ] **Community & Sharing**: Option to securely share data with health professionals or family.
|
|
|
|
---
|
|
**Tech Stack Targets:**
|
|
- Frontend: Vite + React + TypeScript
|
|
- Backend: Rust (Axum / Tokio / SeaORM)
|
|
- Database: SQLite3 (WAL mode)
|
|
- AI: Gemini / OpenAI / Anthropic API (for interpretation)
|