Research

Engineering validation

I record what the software already does, and what my automated tests actually checked. A passing test is not diagnostic accuracy.

Illustration of engineering checks. Not a clinical accuracy result.

Printed engineering checks, a geometry diagram, and a caliper on a lab table.

What I have tested

Seventeen automated tests across these suites, dated 2026-10-19. Summary: test summary. Full log: test log.

Passed

Geometry

I checked Lovibond angle, depth ratio, and related math on known coordinates.

Passed

Quality

I reject a finger that is too small, blur, motion, and extreme exposure. An aligned fixture passes.

Passed

Fusion and the one-image rule

I reject a one-image patient conclusion. I also exercise the multi-finger path.

Passed

Stub withhold

I check that labels stay consistent with keeping stub results research-only. A stub may not look clinical.

What is not established

Passing engineering tests does not prove clinical performance.

Clinical accuracy

I have not established diagnostic utility, population performance, or calibrated uncertainty. Classification bands in code are provisional.

Fairness

I have not established fairness across skin tones. I do not claim demographic fairness from these tests.

Landmark AI

Trained landmark models are not the default path. A number from placeholders is not proof I found the anatomy.

Cameras and lighting

Do lighting, pigmentation, and camera quality change landmark error, and therefore the angle or depth-ratio numbers? I have not proven the system across devices.

How the path is built