The MEDIQA challenge is an ACL-BioNLP 2019 shared task aiming to attract further research efforts in Natural Language Inference (NLI), Recognizing Question Entailment (RQE), and their applications in medical Question Answering (QA).
- Website: https://sites.google.com/view/mediqa2019
- Mailing list: https://groups.google.com/forum/#!forum/bionlp-mediqa
- Overview paper: https://www.aclweb.org/anthology/W19-5039.pdf
- Post-challenge round on AICrowd: You can submit your runs here https://www.aicrowd.com/organizers/mediqa-acl-bionlp
- Task 1 (NLI): https://physionet.org/content/mednli-bionlp19/1.0.1/
- Task 2 (RQE): https://github.com/abachaa/MEDIQA2019/tree/master/MEDIQA_Task2_RQE
- Task 3 (QA): https://github.com/abachaa/MEDIQA2019/tree/master/MEDIQA_Task3_QA
This work is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0). If you use the MEDIQA 2019 datasets, please cite our paper:
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Asma Ben Abacha, Chaitanya Shivade, and Dina Demner-Fushman. Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering. ACL-BioNLP 2019.
@inproceedings{MEDIQA2019, author = {Asma {Ben Abacha} and Chaitanya Shivade and Dina Demner{-}Fushman}, title = {Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering}, booktitle = {ACL-BioNLP 2019}, year = {2019}}
- https://github.com/abachaa/MEDIQA2019/tree/master/Eval_Scripts
- https://github.com/abachaa/MEDIQA2019/tree/master/Eval_Scripts/data
https://www.aicrowd.com/organizers/mediqa-acl-bionlp
72 teams have participated, the results are available here:
- https://www.aicrowd.com/challenges/mediqa-2019-natural-language-inference-nli/leaderboards
- https://www.aicrowd.com/challenges/mediqa-2019-recognizing-question-entailment-rqe/leaderboards
- https://www.aicrowd.com/challenges/mediqa-2019-question-answering-qa/leaderboards
- Asma Ben Abacha: asma.benabacha AT gmail.com https://sites.google.com/site/asmabenabacha/