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What really changed in digital pathology this year—and what still needs work?
As we close out 2025 and step into 2026, I wanted to pause, reflect, and share what I’ve seen shift from theory to real-world practice across labs, conferences, and clinical workflows.
I look back at the most meaningful developments in digital pathology and AI in 2025—from wider adoption of primary diagnosis on digital slides to more grounded, evidence-driven use of AI tools. We’ve moved past hype and pilots and started asking harder questions about validation, workflow integration, regulation, and trust.
I also share what I believe matters most as we move into 2026: building real-world evidence, upskilling pathologists, and focusing on tools that genuinely support patient care rather than distract from it.
This episode is for anyone navigating change in pathology and wondering where to invest their time, energy, and curiosity next.
Episode Highlights:
- [00:00–02:10] Why 2025 marked a turning point for digital pathology adoption
- [02:10–05:40] From pilot projects to clinical workflows: what actually changed
- [05:40–08:30] How AI usage shifted toward triage, quantification, and decision support
- [08:30–11:45] Why validation and real-world evidence became central topics
- [11:45–14:20] The growing role of pathologists in AI governance and quality assurance
- [14:20–17:10] Lessons from conferences, labs, and conversations worldwide
- [17:10–20:00] What I expect to see more of in 2026—and what I hope we leave behind
Key Takeaways:
- Digital pathology is no longer experimental—it’s becoming routine in more labs.
- AI tools are shifting from novelty to practical clinical support.
- Validation, regulation, and workflow fit matter more than algorithm performance alone.
- Training and continuous learning are now essential career components for pathologists.
- 2026 will reward teams that test, measure, and iterate thoughtfully.
Resources Mentioned
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