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Video Tutorial – Rapid AI Development with Concentriq Embeddings: Zero-Shot Tumor Detection Example

Corey Chivers
By Corey Chivers | December 19, 2024

Pathology AI development without the data bottleneck? It’s here.

Building AI models for tissue classification in histopathology has traditionally meant assembling large, hand-annotated datasets—a time-consuming and resource-heavy process. But what if you didn’t need those massive datasets? With Concentriq Embeddings and PLIP, a multimodal vision-language foundation model, you can build a zero-shot tissue classification model in minutes—no annotated training data required.

How does it work?

Watch this short tutorial and learn how to use Concentriq Embeddings to generate slide-level predictions and heatmaps that visually highlight tumor regions—all without the data bottleneck. It’s like going from zero to hero—but in this case, zero is the hero.

Resources

Explore the Jupyter Notebook

Learn more about Concentriq Embeddings

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