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PathVQA

Is it possible to develop an "AI Pathologist" to pass the board-certified examination of the American Board of Pathology? To achieve this goal, we build a medical visual question answering (VQA) dataset where the AI agent is presented with a pathology image together with a question and is asked to give the correct answer. The dataset contains 32,799 open-ended questions from 4,998 pathology images.

The dataset is built from two publicly-available pathology textbooks: “Textbook of Pathology" and “Basic Pathology", and a publicly-available digital library: Pathology Education Informational Resource (PEIR). The copyrights of images and captions belong to the publishers and authors of these two books, and the owners of the PEIR digital library.

The paper is available here

If you find this dataset useful, please cite:

@article{he2020pathvqa,
  title={PathVQA: 30000+ Questions for Medical Visual Question Answering},
  author={He, Xuehai and Zhang, Yichen and Mou, Luntian and Xing, Eric and Xie, Pengtao},
  journal={arXiv preprint arXiv:2003.10286},
  year={2020}
}

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  • Python 82.2%
  • Shell 17.8%