Research
How DiagnovisAI is evaluated before any performance claims are made.
Clinical validation
AI performance does not automatically transfer across populations, scanners and hospitals.
DiagnovisAI is entering a two-phase validation at a national referral hospital in Uganda: retrospective testing on archived Ugandan studies, then a prospective pilot in the live reporting pathway. Both are subject to independent ethics review.
Partnerships & Collaborations
Clinical and academic collaboration is how responsible medical AI gets built.
Built with partners, not in isolation
We are developing clinical and academic collaborations for evaluation and responsible introduction. Details will be published as they are formalised.
Start the conversation
If your institution works in medical imaging, AI evaluation, or health-systems strengthening in East Africa, we would like to hear from you.
Publications
Peer-reviewed output from the Diagnovis research programme.
Peer-reviewed publications will be added here as our research programme matures.
Resources
Demos & videos
Recorded demonstrations are being prepared. Until then, see it live.
Educational content
Material on AI-assisted imaging and radiologist-supported workflows is in review.
External reading
Reading from the wider field of medical imaging and AI, being compiled.
Questions about our validation approach?
We welcome scrutiny. Bring yours to a working session.
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