From cc8941d881c8119ed0d7cd1b120b95ee92a2c7f3 Mon Sep 17 00:00:00 2001 From: dartrevan Date: Thu, 29 Oct 2020 15:23:43 +0300 Subject: [PATCH] Create README.md (#8089) --- model_cards/cimm-kzn/endr-bert/README.md | 41 ++++++++++++++++++++++++ 1 file changed, 41 insertions(+) create mode 100644 model_cards/cimm-kzn/endr-bert/README.md diff --git a/model_cards/cimm-kzn/endr-bert/README.md b/model_cards/cimm-kzn/endr-bert/README.md new file mode 100644 index 00000000000..82d51a6da90 --- /dev/null +++ b/model_cards/cimm-kzn/endr-bert/README.md @@ -0,0 +1,41 @@ +## RuDR-BERT + + EnDR-BERT - Multilingual, Cased, which pretrained on the collecting of consumer comments on drug administration from [2]. Pre-training was based on the [original BERT code](https://github.com/google-research/bert) provided by Google. In particular, Multi-BERT was for used for initialization; vocabulary of Russian subtokens and parameters are the same as in Multi-BERT. Training details are described in our paper. \ + link: https://yadi.sk/d/-PTn0xhk1PqvgQ + + + ## Citing & Authors + + If you find this repository helpful, feel free to cite our publication: + + [1] Tutubalina E, Alimova I, Miftahutdinov Z, et al. The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews.//Bioinformatics. - 2020. + + preprint: https://arxiv.org/abs/2004.03659 + ``` + @article{10.1093/bioinformatics/btaa675, + author = {Tutubalina, Elena and Alimova, Ilseyar and Miftahutdinov, Zulfat and Sakhovskiy, Andrey and Malykh, Valentin and Nikolenko, Sergey}, + title = "{The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews}", + journal = {Bioinformatics}, + year = {2020}, + month = {07}, + issn = {1367-4803}, + doi = {10.1093/bioinformatics/btaa675}, + url = {https://doi.org/10.1093/bioinformatics/btaa675}, + note = {btaa675}, + eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaa675/33539752/btaa675.pdf}, + } + ``` + [2] Tutubalina, EV and Miftahutdinov, Z Sh and Nugmanov, RI and Madzhidov, TI and Nikolenko, SI and Alimova, IS and Tropsha, AE Using semantic analysis of texts for the identification of drugs with similar therapeutic effects.//Russian Chemical Bulletin. – 2017. – Т. 66. – №. 11. – С. 2180-2189. + [link to paper](https://www.researchgate.net/profile/Elena_Tutubalina/publication/323751823_Using_semantic_analysis_of_texts_for_the_identification_of_drugs_with_similar_therapeutic_effects/links/5bf7cfc3299bf1a0202cbc1f/Using-semantic-analysis-of-texts-for-the-identification-of-drugs-with-similar-therapeutic-effects.pdf) + ``` + @article{tutubalina2017using, + title={Using semantic analysis of texts for the identification of drugs with similar therapeutic effects}, + author={Tutubalina, EV and Miftahutdinov, Z Sh and Nugmanov, RI and Madzhidov, TI and Nikolenko, SI and Alimova, IS and Tropsha, AE}, + journal={Russian Chemical Bulletin}, + volume={66}, + number={11}, + pages={2180--2189}, + year={2017}, + publisher={Springer} + } + ```