Bo Wang: How Recent Advances in Foundation Models Are Redefining What’s Possible in Cancer Diagnostics
Bo Wang, Chief AI Scientist at University Health Network, shared a post on LinkedIn:
“Just had the pleasure of being interviewed by Nature Portfolio on the rise of AI in digital pathology. With growing workloads and global shortages of pathologists, the field is turning to AI not as a luxury—but as a necessity.
In the article, I discuss how recent advances in foundation models like UNI-2 and CONCH are redefining what’s possible in cancer diagnostics. Trained on hundreds of millions of pathology patches, these models go beyond classification: they enable molecular subtyping, caption generation, and even zero-shot inference.
But while the hype is real, so are the challenges. Cross-site generalization, lack of external validation, and regulatory hurdles remain major barriers. We must invest in robust benchmarking, multi-institutional trials, and trustworthy model design to ensure AI truly supports—not replaces—clinical judgment.
Digital pathology isn’t the future—it’s already here. Let’s make it safe, scalable, and equitable.
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