PathPT improves few-shot rare cancer subtyping by using zero-shot vision-language models to create tile-level pseudo-labels and learning prompt tokens with spatial context, outperforming standard MIL baselines when the backbone has strong zero-shot grounding.
Deep learning-based histotype diagnosis of ovarian carcinoma whole-slide pathology images.Modern Pathology, 35(12):1983–1990, 2022
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Boosting Pathology Foundation Models via Few-shot Prompt-tuning for Rare Cancer Subtyping
PathPT improves few-shot rare cancer subtyping by using zero-shot vision-language models to create tile-level pseudo-labels and learning prompt tokens with spatial context, outperforming standard MIL baselines when the backbone has strong zero-shot grounding.