Two weeksOvernight
Automated validation against held-out production data shortened the wait for model-performance results.
Imaging AI · An interactive case study
One model.
A platform around it.
How I grew a partner-supplied AI proof into a production platform for medical imaging.
The little-proof questionWhat does it take to turn one imaging model into a platform a team can operate?
Explore the evolution
Chapter 01
Make the first connection.
The starting point was one partner-supplied model. The work was connecting it to the imaging systems around it.
THE FIRST CAPABILITY
One partner model.
A connection to the clinical workflow.
Connect a model to a real workflow.
The work behind the illustration
Built for more than
a single model.
Reported career results from the platform and the work around it.
100+ NLP models
A real-time language-processing framework supported physician notifications, data curation, and image-model evaluation.
~6 AI partners
Helped partners deploy and validate their models, with queued DICOM exports replacing manual data dumps.
My contribution
The connective work.
I provided architectural direction and coordinated delivery across clinical, engineering, product, partner, and executive groups—while building the platform, integrations, and tools that made the work possible.
About this case study
This is an independent, interactive account of my work at vRad, based on my résumé and personal account. The diagrams explain capabilities and relationships; they are not a reconstruction of proprietary architecture or a live clinical system.
The displayed outcomes are reported career results, not measurements generated by this website. The 100+ figure refers specifically to NLP models. No patient data or employer code is used.