PubMedQA Homepage (original) (raw)

About

The task of PubMedQA is to answer research questions with yes/no/maybe (e.g.: Do preoperative statins reduce atrial fibrillation after coronary artery bypass grafting?) using the corresponding abstracts.

For more details about PubMedQA, please refer to this paper:

Dataset

PubMedQA has 1k expert labeled, 61.2k unlabeled and 211.3k artificially generated QA instances.

Please visit our GitHub repository to download the dataset:

Submission

To submit your model, please follow the instructions in the GitHub repository.

Citation

If you use PubMedQA in your research, please cite our paper by:

@inproceedings{jin2019pubmedqa, title={PubMedQA: A Dataset for Biomedical Research Question Answering}, author={Jin, Qiao and Dhingra, Bhuwan and Liu, Zhengping and Cohen, William and Lu, Xinghua}, booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)}, pages={2567--2577}, year={2019} }