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.