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Insights
Practical guides to healthcare data for research and AI.
How to license, de-identify and validate medical data, and what researchers say they need, from the team behind BCONZ's data platform.
Data licensing
Licensing medical imaging data for AI: a buyer's checklist
What to agree before licensing medical imaging data for AI: rights, permitted use, model ownership, data specification, de-identification and price.
3 November 2026 · 8 min read
Read articleHealthcare AI
External validation for medical AI: what a good test dataset looks like
What makes a test set truly external for medical AI: independent sites, no patient overlap, a representative population and a sound reference standard.
3 November 2026 · 7 min read
Read articleData partnerships
Licensing de-identified hospital data for research: a guide for hospitals and labs
How hospitals, labs and imaging centres can make de-identified data available for research and AI: demand, governance, de-identification and revenue.
3 November 2026 · 7 min read
Read articleData governance
De-identifying medical images: why removing the DICOM header isn't enough
Names and dates can sit in image pixels, report text and private DICOM tags. What full de-identification of medical images involves, and what to ask.
2 November 2026 · 7 min read
Read articleHealthcare AI
Free medical imaging datasets: where they fall short for commercial AI
MIMIC-CXR, CheXpert and ChestX-ray14 trained a generation of models. Where public imaging datasets fall short for products, and what to use alongside them.
2 November 2026 · 8 min read
Read articleResearch
What 1,959 research papers say about missing healthcare data
We analysed the limitations sections of 1,959 recent papers that state a data gap. 47% cite a single-centre design. What researchers say they need next.
2 November 2026 · 6 min read
Read articleStay informed
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