Technology 4 min read

Doctors Who Code: From GitHub to Medical AI

A practical path for physicians who want to move from GitHub basics to building real medical AI projects.

By Dr. Chukwuma Onyeije, MD, FACOG

Maternal-Fetal Medicine Specialist & Medical Director, Atlanta Perinatal Associates

Founder, Doctors Who Code · OpenMFM.org · CodeCraftMD · · 4 min read

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Doctors Who Code: From GitHub to Medical AI

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Most physicians do not need another speech about why technology matters in medicine.

We already live inside broken systems. We already feel the friction. The real question is whether physicians will keep adapting to tools designed by other people, or whether more of us will learn to build.

This series is a practical path into that work.

It starts with GitHub, not because version control is glamorous, but because unfinished work needs a real home. It then moves into project scoping, structured clinical data, and the realities of finding and building medical AI tools that are actually worth your time.

This is not a series about becoming a full-time software engineer. It is a series about technical ownership. About learning enough to turn a recurring clinical frustration into a tool, a workflow, or a first real project.

If you are a physician who has been circling this world without entering it, start here.

Series Roadmap

  1. Stop Lurking: Why Physicians Should Start GitHub Before They Feel Ready
  2. GitHub for Physicians: Why Version Control Changes How You Build
  3. Your First Week on GitHub as a Physician: A Practical Starter Plan
  4. Three GitHub Projects Physicians Can Actually Finish
  5. JSON for Physicians: The Structured Data Your Clinical AI Actually Needs
  6. Navigating Medical AI on GitHub: What Is Worth Your Time
  7. Your First Medical AI Project on GitHub: How to Choose One You Will Actually Finish
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Chukwuma Onyeije, MD, FACOG

Chukwuma Onyeije, MD, FACOG

Maternal-Fetal Medicine Specialist

MFM specialist at Atlanta Perinatal Associates. Founder of CodeCraftMD and OpenMFM.org. I write about building physician-owned AI tools, clinical software, and the case for doctors who code.