Deep Neural Models for Medical Concept Normalization in User-Generated Texts

PsyTar folds used for experiments in the paper "Deep Neural Models for Medical Concept Normalization in User-Generated Texts" to be published at ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Student Research Workshop.

All other datasets used in the paper can be found in the following places:

Cadec random: https://zenodo.org/record/55013#.XPE1MC1eN24<br>
Cadec custom: https://yadi.sk/d/GZoWm1wBxzyW_w

SMM4H dataset: in the paper "Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H) - 2017 shared task"<br>
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Bibtex:

@inproceedings{miftahutdinov2019,<br>
title = "Deep Neural Models for Medical Concept Normalization in User-Generated Texts",<br>
author = "Miftahutdinov, Zulfat and Tutubalina, Elena",<br>
booktitle = "Proceedings of {ACL} 2019, Student Research Workshop",<br>
month = jul,<br>
year = "2019",<br>
address = "Florence, Italy",<br>
publisher = "Association for Computational Linguistics",<br>
}