MEDIQA2019

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

Datasets

• 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

If you use these datasets, please cite our overview paper:

Reference

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}
  
}

Evaluation Scripts

• https://github.com/abachaa/MEDIQA2019/tree/master/Eval_Scripts
• https://github.com/abachaa/MEDIQA2019/tree/master/Eval_Scripts/data

Projects@AIcrowd

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

Contact Information

• Asma Ben Abacha: asma.benabacha AT gmail.com https://sites.google.com/site/asmabenabacha/