Pathology foundation models deliver strong in-distribution prostate cancer grading performance but exhibit large drops under cross-site image appearance shifts while remaining relatively robust to label distribution shifts.
Colorectal cancer risk stratification on histological slides based on survival curves predicted by deep learning
2 Pith papers cite this work. Polarity classification is still indexing.
verdicts
UNVERDICTED 2representative citing papers
H-optimus-1 achieves the strongest externally validated survival prediction from histopathology images, with second-generation PFMs outperforming first-generation counterparts and a compact distilled model offering efficiency gains.
citing papers explorer
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Evaluating Computational Pathology Foundation Models for Prostate Cancer Grading under Distribution Shifts
Pathology foundation models deliver strong in-distribution prostate cancer grading performance but exhibit large drops under cross-site image appearance shifts while remaining relatively robust to label distribution shifts.
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Benchmarking Pathology Foundation Models for Breast Cancer Survival Prediction
H-optimus-1 achieves the strongest externally validated survival prediction from histopathology images, with second-generation PFMs outperforming first-generation counterparts and a compact distilled model offering efficiency gains.