language: | |
- en | |
bigbio_language: | |
- English | |
license: cc-by-4.0 | |
multilinguality: monolingual | |
bigbio_license_shortname: CC_BY_4p0 | |
pretty_name: AskAPatient | |
homepage: https://zenodo.org/record/55013 | |
bigbio_pubmed: True | |
bigbio_public: True | |
bigbio_tasks: | |
- NAMED_ENTITY_RECOGNITION | |
- NAMED_ENTITY_DISAMBIGUATION | |
# Dataset Card for AskAPatient | |
## Dataset Description | |
- **Homepage:** https://zenodo.org/record/55013 | |
- **Pubmed:** True | |
- **Public:** True | |
- **Tasks:** NER,NED | |
The AskAPatient dataset contains medical concepts written on social media mapped to how they are formally written in medical ontologies (SNOMED-CT and AMT). | |
## Citation Information | |
``` | |
@inproceedings{limsopatham-collier-2016-normalising, | |
title = "Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation", | |
author = "Limsopatham, Nut and | |
Collier, Nigel", | |
booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", | |
month = aug, | |
year = "2016", | |
address = "Berlin, Germany", | |
publisher = "Association for Computational Linguistics", | |
url = "https://aclanthology.org/P16-1096", | |
doi = "10.18653/v1/P16-1096", | |
pages = "1014--1023", | |
} | |
``` | |