About
Medicine is science in action; AI is more than tooling—it reshapes cognition. This project weaves both into a validated, reusable knowledge system.
What we are building
- Resilient knowledge: Git-powered, versioned content that keeps clinical and AI updates transparent.
- Codified practice: Clinical reasoning frameworks, evidence summaries, and case retrospectives ready for teaching.
- Intelligent assistance: Working notes on how large language models augment research, diagnosis, and learning.
Principles
| Value | What it means |
|---|---|
| Responsible innovation | Ethics-first adoption of AI in medical decision making |
| Shared wisdom | Invite clinicians, engineers, and researchers to co-review and co-create |
| Verification first | Every claim is traceable to data, literature, or field practice |
Who this is for
- Healthcare professionals: clinicians, medical trainees, translational researchers
- Builders: ML engineers, product teams, and startups in digital health
- Educators: curriculum designers, academic mentors, and continuing education leaders
Content tracks
- Clinics & Research — Evidence distillations, workflow retrospectives, and emergent trend scanning
- Intelligent Tooling — Dialogue logs, automation snippets, and model evaluation field notes
- Knowledge Operations — Course design frameworks, collaboration playbooks, and governance guides
Ways to contribute
- Submit issues/PRs with case studies, literature, or translation improvements
- Share your cross-disciplinary experiments to expand the knowledge graph
- Amplify the project so more domain experts can review and participate
Your voice matters—help us combine the warmth of clinical care with the imagination of modern computing.