Built for clinical reality
Every MediXtract project follows an iterative and transparent structure designed around the documentation and medical expert time.
We build intelligent data collection systems and evaluate their performance at scale. This is a structured partnership: starting with clinical engagement, iterating through tuning cycles, and continuing in production.
A phased approach to building intelligent data collection systems.
Understanding the landscape.
Direct collaboration with specialists to understand data structure and terminology. We categorise variables to set the technical foundation.
Iterative refinement.
Comparing AI outputs against human-validated ground truth. We update the logic based on discrepancy classification (Improvements vs. Issues).
Transparent metrics.
Generating a structured report on precision, recall, and consistency. This report serves as the basis for expert feedback.
Closing the loop.
Medical professionals resolve ambiguities and validate cohort results via the Architect. These insights feed directly into the next cycle.
Each cycle represents 80 team hours:
Clinicians are co-designers from day one.
Performance reports are generated every cycle.
Assisting teams in building better variables.
Governance (Anonymisation, DLP) is built-in.