| language: | |
| - en | |
| bigbio_language: | |
| - English | |
| license: unknown | |
| multilinguality: monolingual | |
| bigbio_license_shortname: UNKNOWN | |
| pretty_name: MQP | |
| homepage: https://github.com/curai/medical-question-pair-dataset | |
| bigbio_pubmed: False | |
| bigbio_public: True | |
| bigbio_tasks: | |
| - SEMANTIC_SIMILARITY | |
| # Dataset Card for MQP | |
| ## Dataset Description | |
| - **Homepage:** https://github.com/curai/medical-question-pair-dataset | |
| - **Pubmed:** False | |
| - **Public:** True | |
| - **Tasks:** STS | |
| Medical Question Pairs dataset by McCreery et al (2020) contains pairs of medical questions and paraphrased versions of | |
| the question prepared by medical professional. Paraphrased versions were labelled as similar (syntactically dissimilar | |
| but contextually similar ) or dissimilar (syntactically may look similar but contextually dissimilar). Labels 1: similar, 0: dissimilar | |
| ## Citation Information | |
| ``` | |
| @article{DBLP:journals/biodb/LiSJSWLDMWL16, | |
| author = {Krallinger, M., Rabal, O., Lourenço, A.}, | |
| title = {Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs}, | |
| journal = {KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining}, | |
| volume = {3458–3465}, | |
| year = {2020}, | |
| url = {https://github.com/curai/medical-question-pair-dataset}, | |
| doi = {}, | |
| biburl = {}, | |
| bibsource = {} | |
| } | |
| ``` | |