PathVLM-Eval: Evaluation of open vision language models in histopathology.

ABSTRACT: The emerging trend of vision language models (VLMs) has introduced a new paradigm in artificial intelligence (AI). However, their evaluation has predominantly focused on general-purpose datasets, providing a limited understanding of their effectiveness in specialized domains. Medical imaging, particularly digital pathology, could significantly benefit from VLMs for histological interpretation and diagnosis, enabling pathologists to use a complementary tool for faster morecomprehensive reporting and efficient healthcare service. In this work, we are interested in benchmarking VLMs on histopathology image understanding. We present an extensive evaluation of recent VLMs on the PathMMU dataset, a domain-specific benchmark that includes subsets such as PubMed, SocialPath, and EduContent. These

SUBMITTER: Gilal NU 

PROVIDER: S-EPMC12276438 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature