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> <br> 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> }