Тутубалина Елена Викторовна

Публикации¹⁴

• Статья Loukachevitch N., Manandhar S., Baral E., Rozhkov I., Braslavski P., Ivanov V., Batura T., Tutubalina E. NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities // Bioinformatics. 2023. Vol. 39. No. 4. Article btad161. doi
• Статья Alimova I., Tutubalina E., Nikolenko S. I. Cross-Domain Limitations of Neural Models on Biomedical Relation Classification // IEEE Access. 2022. Vol. 10. P. 1432-1439. doi
• Статья Sakhovskiy A., Tutubalina E. Multimodal model with text and drug embeddings for adverse drug reaction classification // Journal of Biomedical Informatics. 2022. Vol. 135. Article 104182. doi
• Глава книги Alekseev A., Tutubalina E., Kwon S., Nikolenko S. I. Near-Zero-Shot Suggestion Mining with a Little Help from WordNet, in: Analysis of Images, Social Networks and Texts. 10th International Conference, AIST 2021, Tbilisi, Georgia, December 16–18, 2021, Revised Selected Papers / Ed. by E. Burnaev, D. I. Ignatov, S. Ivanov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, J. Saramäki, A. Savchenko, E. Tsymbalov, E. Tutubalina. Cham : Springer, 2022. doi P. 23-36. doi
• Глава книги Alimova I., Tutubalina E. Selection of Pseudo-Annotated Data for Adverse Drug Reaction Classification Across Drug Groups, in: Analysis of Images, Social Networks and Texts. 10th International Conference, AIST 2021, Tbilisi, Georgia, December 16–18, 2021, Revised Selected Papers / Ed. by E. Burnaev, D. I. Ignatov, S. Ivanov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, J. Saramäki, A. Savchenko, E. Tsymbalov, E. Tutubalina. Cham : Springer, 2022. doi P. 37-44. doi
• Статья Banda J. M., Tekumalla R., Wang G., Yu J., Liu T., Ding Y., Artemova E., Tutubalina E., Chowell G. A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration // Epidemiologia. 2021. Vol. 2. No. 3. P. 315-324. doi
• Статья Magge A., Tutubalina E., Miftahutdinov Z., Алимова И. С., Dirkson A., Verberne S., Weissenbacher D., Gonzalez-Hernandez G. DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter // Journal of the American Medical Informatics Association : JAMIA. 2021. Vol. 28. No. 10. P. 2184-2192. doi
• Глава книги Malykh V., Porplenko D., Tutubalina E. Generating Sport Summaries: A Case Study for Russian, in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers / Ed. by W. M. van der Aalst, V. Batagelj, D. I. Ignatov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, I. A. Lomazova, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Cham: Springer, 2021. doi P. 149-161. doi
• Глава книги Loukachevitch N., Artemova E., Batura T., Braslavski P., Denisov I., Ivanov V., Manandhar S., Pugachev A., Tutubalina E. NEREL: A Russian Dataset with Nested Named Entities, Relations and Events, in: International Conference Recent Advances in Natural Language Processing, RANLP 2021. Shoumen, BULGARIA: Association for Computational Linguistics, 2021. P. 876-886.
• Глава книги Sakhovskiy A., Izhevskaya A., Pestova A., Tutubalina E., Malykh V., Smurov I., Artemova E. RuSimpleSentEval-2021 Shared Task: Evaluating Sentence Simplification for Russian, in: Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference “Dialogue” (2021) Issue 20: Основной том. -, 2021. Ch. 161. P. 607-617.
• Статья Tutubalina E., Алимова И. С., Мифтахутдинов З., Sakhovskiy A., Malykh V., Nikolenko S. I. The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews // Bioinformatics. 2021. Vol. 37. No. 2. P. 243-249. doi
• Статья Alimova l., Tutubalina E. Multiple features for clinical relation extraction: A machine learning approach // Journal of Biomedical Informatics. 2020. Vol. 103. P. 1-9. doi
• Глава книги Shenbin I., Alekseev A., Tutubalina E., Malykh V., Nikolenko S. I. RecVAE: A new variational autoencoder for top-n recommendations with implicit feedback, in: WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining. Association for Computing Machinery (ACM), 2020. doi P. 528-536. doi
• Глава книги Artemova E., Batura T., Golenkovskaya A., Ivanin V., Ivanov V., Sarkisyan V., Smurov I., Tutubalina E. So What’s the Plan? Mining Strategic Planning Documents, in: Digital Transformation and Global Society. DTGS 2020 Vol. 1242. Springer, 2020. doi P. 208-222. doi