Physician-Developer Academy

Medicine needs more physicians who can build.

Doctors Who Code is a guided learning platform for physicians who want to understand software, use AI with judgment, and build clinical tools that survive contact with real practice.

Written from
Maternal-Fetal Medicine practice
Built by
Chukwuma Onyeije, MD, FACOG

Learning Paths

Begin with the gap you need to close.

The archive contains the full body of work. These paths give selected articles an instructional order and a project at the end.

Featured Start Here Guide

One path. One course. One finished build.

Do not begin by trying to understand the entire software landscape. Choose the path that matches your present work. Complete its first course in order. Build the project before adding another course.

Open Start Here
  1. 01
    Locate the gapCode, AI workflow design, or medical software.
  2. 02
    Follow the sequenceLessons are ordered by dependency, not publication date.
  3. 03
    Produce the artifactA utility, workflow map, or tested calculator.

Physician-Built Projects

The argument is visible in the systems.

The platform teaches from working examples built inside clinical practice, not from abstract product exercises.

Latest from the Journal

The work continues between courses.

Browse all articles
A physician-developer in a white coat holding a glowing GitHub Gist icon, connected by streams of light to clinical diagrams, decision trees, and code panels around him
Physician Development Featured

GitHub Gists: The Most Underrated Tool Every Physician-Developer Should Be Using

GitHub Gists look like scratch space for code snippets. Used correctly, they become a version-controlled clinical reference library that decks, apps, and blog posts can all cite from a single source.

· 9 min read
githubgithub-gistsphysician-developer
Physician reviewing a clinical AI observability dashboard showing sensitivity drift, calibration curves, and subgroup performance alongside a diagnostic imaging panel
AI in Medicine Featured

FDA Clearance Is Not a Monitoring Plan

Clinical AI can fail without crashing. Physician-developers must build the monitoring, outcome linkage, and human checkpoints that keep cleared software safe after deployment.

· 18 min read
clinical-aiphysician-developermodel-monitoring
Physician using a structured clinical documentation workstation in a hospital corridor
Clinical Workflow Featured

From Meetings to Modules: Redefining Clinical Coordination

Clinical teams do not move slowly because clinicians are slow. They move slowly because pages, meetings, and verbal handoffs force physicians to keep re-explaining decisions that software should carry forward.

· 6 min read
clinical-workflowclinical-coordinationdocumentation-as-code
Physician-developer reviewing maternal-fetal medicine documentation and software code at a dual-monitor workstation
AI in Medicine Featured

Surviving the AI-Native Transformation: A Physician-Developer's Guide

AI makes clinical software cheap to produce. It does not make it safe. Physician-developers must build systems in which speed remains subordinate to evidence, judgment, and the doctor-patient relationship.

· 6 min read
ai-nativeclinical-aiphysician-developer