Datasets:
Tasks:
Visual Question Answering
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
medical
License:
flaviagiammarino
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and the owners of the PEIR digital library.<br>
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![image](image.png)<br>
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**Paper:** [PathVQA: 30000+ Questions for Medical Visual Question Answering](https://arxiv.org/abs/2003.10286)<br>
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**Repository:** [PathVQA Official GitHub Repository](https://github.com/UCSD-AI4H/PathVQA)<br>
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**Leaderboard:** [Papers with Code Leaderboard](https://paperswithcode.com/sota/medical-visual-question-answering-on-pathvqa)
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The data was obtained from the updated Google Drive link shared by the authors on Feb 15, 2023,
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see the [commit](https://github.com/UCSD-AI4H/PathVQA/commit/117e7f4ef88a0e65b0e7f37b98a73d6237a3ceab)
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in the GitHub repository. This version of the dataset contains a total of 5,004 images and 32,795 question-answer pairs.
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Out of the 5,004 images, 4,289 images are referenced by a question-answer pair, while 715 images are not used.
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There are a few
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After dropping the duplicate image-question-answer triplets, the dataset contains 32,632 question-answer pairs on 4,289 images.
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## Dataset Description
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PathVQA is a dataset of question-answer pairs on pathology images. The dataset is intended to be used for training and testing
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Medical Visual Question Answering (VQA) systems. The questions contained in the dataset are similar to those in the American
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Board of Pathology (ABP) test. The dataset includes both open-ended questions and binary "yes/no" questions. The dataset is
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built from two publicly-available pathology textbooks: "Textbook of Pathology" and "Basic Pathology", and a publicly-available
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digital library: "Pathology Education Informational Resource" (PEIR). The copyrights of images and captions belong to the
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publishers and authors of these two books, and the owners of the PEIR digital library.<br>
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![image](image.png)<br>
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**Repository:** [PathVQA Official GitHub Repository](https://github.com/UCSD-AI4H/PathVQA)<br>
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**Paper:** [PathVQA: 30000+ Questions for Medical Visual Question Answering](https://arxiv.org/abs/2003.10286)<br>
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**Leaderboard:** [Papers with Code Leaderboard](https://paperswithcode.com/sota/medical-visual-question-answering-on-pathvqa)
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### Dataset Summary
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The data was obtained from the updated Google Drive link shared by the authors on Feb 15, 2023,
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see the [commit](https://github.com/UCSD-AI4H/PathVQA/commit/117e7f4ef88a0e65b0e7f37b98a73d6237a3ceab)
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in the GitHub repository. This version of the dataset contains a total of 5,004 images and 32,795 question-answer pairs.
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Out of the 5,004 images, 4,289 images are referenced by a question-answer pair, while 715 images are not used.
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There are a few image-question-answer triplets which occur more than once in the same split (training, validation, test).
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After dropping the duplicate image-question-answer triplets, the dataset contains 32,632 question-answer pairs on 4,289 images.
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#### Supported Tasks and Leaderboards
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