189: Digital Pathology Deployment Decoded the Rigorous 4 Phase Framework

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Sometimes a paper comes out that’s so practical and relevant to what we do in digital pathology that I know we have to talk about it.


In this episode, I dive into “A Guide for the Deployment, Validation and Accreditation of Clinical Digital Pathology Tools” from Geneva University Hospital (HUG) — one of the most useful, real-world frameworks I’ve seen for bringing digital pathology tools safely into clinical practice.


If you’ve ever built an AI model and wondered, “Now what?”, this episode is for you.
Because building the model is often the easy part — deployment is where things get complex.


This guide breaks the process into four practical phases every lab can follow:


1️⃣ Pre-Development – Define your clinical need, project scope, and validation plan before writing a single line of code.
2️⃣ Development – Build and integrate the algorithm in a production-ready environment.
3️⃣ Validation & Hardening – Turn your research code into a reliable, secure, and compliant clinical tool.
4️⃣ Production & Monitoring – Keep the tool validated and performing consistently over time.


We also discuss what makes qualification, validation, and accreditation different — and why that order really matters.
You’ll hear about the multidisciplinary team behind these deployments, especially the deployment engineer (DE) — the technical linchpin who turns AI research into clinical reality.


I share the story of HUG’s H. pylori detection tool, which cut diagnostic time by 26% while maintaining a 0% false negative rate. The team’s secret? Careful planning, quality control, and continuous user feedback — not just great code.


Other highlights include:

• Why integration often takes longer than building the AI model itself
• How to avoid invalidating your validation data
• What continuous performance monitoring looks like in real labs
• And why every lab still needs to do local validation, even with proven tools

If you’re working on digital or computational pathology tools — or just want to understand how AI safely moves from research to routine diagnostics — this episode will give you a roadmap grounded in real experience.


🎧 Listen now to learn how to move from algorithm to accreditation, step by step.


And if you’re just getting started in digital pathology, I’d love to give you my free eBook, Digital Pathology One-on-One: All You Need to Know to Start and Continue Your Digital Pathology Journey.
You’ll find the link to download it in the show notes.


See you in the episode!


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