narhi.tech
All work

Medtech developer

under NDA

Industry

healthcare · an early cancer-diagnosis product

Duration

22 wks

Team

not published

Disciplines

AI · Security · Infrastructure · Development

Task

Get the first version of the algorithm into daily use in a hospital: embed it in the HIS, clear the secured perimeter, retrain the models.

Result

1.4% of false-negative reports sent back for review thanks to the algorithm. A pilot in a working hospital: the tool runs inside the HIS, the clinician sees the result where they already work.

How it went

How it went22 wks

022 wks

  1. stage 1 · 14 wks

    A product around the algorithm, integrated with the HIS

    DevelopmentSecurityInfrastructure

    Task

    The first version of the algorithm had no product around it: no clinician interface, no path into the HIS, no clearance for the perimeter. We worked through the medical formats — CT, MRI, X-ray — and the internals of several HIS platforms. We built patient-data handling to meet the secured perimeter’s requirements.

    Result

    The algorithm runs inside the HIS and is cleared into the hospital’s secured perimeter. The clinician sees the result where they already work.

  2. stage 2 · 8 wks

    Models, MLOps and a team in the hospital

    AIDevelopment

    Task

    Refined the algorithm and retrained the models on the hospital’s data. Set up the MLOps pipeline: data → training → rollout → quality checks. Built the team and the forward-deployed-engineer processes — engineers working next to clinicians.

    Result

    Model updates ship through the pipeline, not by hand. The hospital’s team was hired through our search — some of the engineers work on site: supporting the tool and studying how clinicians use it.

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