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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Localized Medical VQA

Authors: Sergio Tascon-Morales;

Localized Medical VQA

Abstract

This dataset contains 3 sub-datasets with questions about regions for the Medical Visual Question Answering (VQA) task. Traditionally, questions are asked about the entire image. In these datasets, we ask questions about randomly generated regions in an image for fundus images as well as cataract surgery frames and surgeries performed with the DaVinci robot. All three datasets were created using publicly available datasets. For more information and code, visit our GitHub page. If you use this dataset, please cite our work: @inproceedings{tascon2023localized, title={Localized Questions in Medical Visual Question Answering}, author={Tascon-Morales, Sergio and M{\'a}rquez-Neila, Pablo and Sznitman, Raphael}, booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention}, pages={361--370}, year={2023}, organization={Springer} }

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Keywords

VQA, Visual Question Answering, Medical VQA

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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