abachaa/MEDIQA2019
abachaa/MEDIQA2019 has 52 GitHub stars and 18 forks. Star changes are not measured yet. Last checked 2026-11-14 02:13 UTC. Last push 2026-05-13.
Gemessener Sternzuwachs
- in 24h
- Verlauf wird gesammelt
- in 7 days
- Verlauf wird gesammelt
- in 15 days
- Verlauf wird gesammelt
- in 1 month
- Verlauf wird gesammelt
Nettoänderungen in überlappenden Zeiträumen, keine Tagessummen. Fehlende Messwerte bleiben leer. Sterne zeigen Interesse, nicht Qualität.
Über uns
Challenge on Textual Inference and Question Entailment in the Medical Domain https://sites.google.com/view/mediqa2019
EntwicklerwerkzeugeREADME.md
OriginalMEDIQA2019
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
License
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:
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/
Ähnliche Projekte entdecken
codecrafters-io/build-your-own-x
Meistere das Programmieren, indem du deine Lieblingstechnologien von Grund auf neu erschaffst.
562,354 Sternepublic-apis/public-apis
Eine gemeinschaftliche Liste kostenloser APIs
498,804 Sternemorluto/rea
Mit Agenten alles per Reverse Engineering untersuchen, vom Verhalten der Anwendung bis hin zu nativen Binärdateien.
457,800 Sterneopenclaw/openclaw
Die KI, die wirklich Dinge erledigt. Jedes Betriebssystem, jede Plattform. Auf die Hummer-Art. 🦞
394,402 Sterne