Model Card for CONCH \[Journal Link\] \[Open Access Read Link\] \[Github Repo\] \[Cite\] What is CONCH? CONCH (CONtrastive learning from Captions for Histopathology) is a vision language foundation model for histopathology, pretrained on currently the largest histopathology specific vision language dataset of 1.17M image caption pairs. Compare to other vision language foundation models, it demonstrates state of the art performance across 14 tasks in computational pathology ranging from image classification, text to image, and image to text retrieval, captioning, and tissue segmentation. Why use CONCH? : Compared to popular self supervised encoders for computational pathology that were pretrained only on H&E images, CONCH may produce more performant representations for non H&E stained images such as IHCs and special stains, and can be used for a wide range of downstream tasks involving either or both histopathology images and text. CONCH also did not use large public histology slide collections such as TCGA, PAIP, GTEX, etc. for pretraining, which are routinely used in benchmark development in computational pathology. Therefore, we make CONCH available for the research community in…
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