aceA foundation model for clinical-grade computational pathology and rare cancers detection
The analysis of histopathology images with artificial intelligence aims to enable clinical decision support systems and precision medicine. The success of such applications depends on the ability to model the diverse patterns observed in pathology images. To this end, we present Virchow, the largest foundation model for computational pathology to date. In addition to the evaluation of biomarker prediction and cell identification, we demonstrate that a large foundation model enables pan-cancer detection, achievin…
Virchow, the largest pathology foundation model to date, enables pan-cancer detection with 0.95 specimen-level AUC across nine common and seven rare cancers and matches production tissue-specific models using less training data.
Evidence
- Peer-reviewedNature Medicine2024-07-22
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Truvace Impact Record TRV-2026-0385, v1: “A foundation model for clinical-grade computational pathology and rare cancers detection.” Truvace, 2026-07-20. /record/TRV-2026-0385 (accessed at citation time). sha256 99fc6240cbeafc8e…
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