A friendly introduction to Foundation Models for Computational Pathology

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Current advancements in computational pathology (CPath) are using machine learning models trained on diverse tissue images to improve cancer diagnosis, treatment prediction, and more. Notable models like Prov-GigaPath and UNI have achieved state-of-the-art results. Challenges include the need for large, diverse datasets and adapting models for clinical use. Continued development and data partnerships are key to advancing this field.

What AI can tell us about microscope slides – fast.ai