Radiology Specialist · Chief Innovation Officer · Built CBCTScope
I build AIwhere being wrongisn’t an option:medicine.
Most AI advice has nothing at stake. I read medical images every day as an oral and maxillofacial radiologist. I build the training data from my own reads, train the model on it, and test it on cases it has never seen. These essays keep that bar: what a model did on a real case, what it did not, and how to build alone without fooling yourself.
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// Latest writing
One-Person Startup5 minAgent-native imaging: why I gave my CBCT viewer to the agents
Why I built CBCTScope, an open-source local-first CBCT viewer with native AI-agent control over MCP, and why the agent gets navigation verbs but never a verb that returns a finding.
One-Person Startup11 minHow to tell whether a medical AI ever looked at the image
A detector's verdict moved with a corner marker. A chatbot nearly passed a radiology exam with no images. Four checks that show where an AI's score came from.
One-Person Startup13 minWhy a better AI agent needs more supervision, not less
A capable AI agent makes confident mistakes you only see in the outcome. Why written rules decay, and four checks between an agent and what you cannot undo.
One-Person Startup9 minAutomate the junior work and you stop making experts
Let the AI take the routine cases and nobody becomes senior. The deskilling evidence, the counter-study that changes what it means, and three habits that keep the eye.
One-Person Startup10 minWhy AI has not replaced radiologists: what the demo missed
In 2016 serious people said stop training radiologists. Five years later radiology was short of them. What the forecast measured, what a day contains, and one test.
// Lab Notes
All entries// Browse by series
// Agent-native instruments, open source
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