2024
2023
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Sakhovskiy A.S, Tutubalina E.V., Cross-Lingual Transfer Learning in Drug-Related Information Extraction from User-Generated Texts//Programming and Computer Software. - 2023. - Vol.49, Is.7. - P.590-595.
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Somov O, Tutubalina E., Shifted PAUQ: Distribution shift in text-to-SQL//GenBench 2023 - GenBench: 1st Workshop on Generalisation (Benchmarking) in NLP, Proceedings. - 2023. - Vol., Is.. - P.112-129.
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Sakhovskiy A, Semenova N, Kadurin A, Graph-Enriched Biomedical Entity Representation Transformer//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2023. - Vol.14163 LNCS, Is.. - P.109-120.
2021
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Alimova I, Tutubalina E, Nikolenko S.I., Cross-domain Limitations of Neural Models on Biomedical Relation Classification//IEEE Access. - 2021. - Vol., Is.. - .
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Tutubalina E, Alimova I, Miftahutdinov Z, The Russian Drug Reaction Corpus and neural models for drug reactions and effectiveness detection in user reviews//Bioinformatics (Oxford, England). - 2021. - Vol.37, Is.2. - P.243-249.
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Magge A, Tutubalina E, Miftahutdinov Z, 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, Is.10. - P.2184-2192.
2020
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Alekseev A, Tutubalina E, Malykh V, Improving unsupervised neural aspect extraction for online discussions using out-of-domain classification//Journal of Intelligent and Fuzzy Systems. - 2020. - Vol.39, Is.2. - P.2487-2496.
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Alimova I, Tutubalina E., Multiple features for clinical relation extraction: A machine learning approach//Journal of Biomedical Informatics. - 2020. - Vol.103, Is.. - Art. № 103382.
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Alimova I, Tutubalina E, Kirillovich A., Cross-lingual transfer learning for semantic role labeling in russian//Proceedings of the International Conference Computational Linguistics in Bulgaria. - 2020. - Vol., Is.. - P.72-80.
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Ivanin V.A, Artemova E.L, Batura T.V, Rurebus-2020 shared task: Russian relation extraction for business//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2020. - Vol.2020-June, Is.19. - P.416-431.
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Sakhovskiy A, Tutubalina E, Solovyev V, Topic Modeling as a Method of Educational Text Structuring//Proceedings - International Conference on Developments in eSystems Engineering, DeSE. - 2020. - Vol.2020-December, Is.. - P.399-405.
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Miftahutdinov Z, Alimova I, Tutubalina E., On biomedical named entity recognition: Experiments in interlingual transfer for clinical and social media texts//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2020. - Vol.12036 LNCS, Is.. - P.281-288.
2019
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Khasianov, A., Alimova, I., Marchenko, A., Nurhambetova, G., Tutubalina, E., Zuev, D. Lawyer's Intellectual Tool for Analysis of Legal Documents in Russian//Proceedings - 2018 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2018. - 2019. - Vol., Is.. - P.42-46.
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Alimova I, Tutubalina E., A comparative study on feature selection in relation extraction from electronic health records//CEUR Workshop Proceedings. - 2019. - Vol.2523, Is.. - P.34-45.
- Nugmanov Ramil, Miftahutdinov Zulfat, Tutubalina Elena, Addressing medical coding of free-text clinical records in English with deep learning//EUROPEAN JOURNAL OF CLINICAL INVESTIGATION. - 2019. - Vol.49, Is.. - P.117-117.
- Nugmanov Ramil, Alimova Ilseyar, Tutubalina Elena, Adverse drug reactions identification in social media posts and electronic health records with neural networks//EUROPEAN JOURNAL OF CLINICAL INVESTIGATION. - 2019. - Vol.49, Is.. - P.116-117.
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Alimova I.S, Tutubalina E.V., Entity-Level Classification of Adverse Drug Reaction: A Comparative Analysis of Neural Network Models//Programming and Computer Software. - 2019. - Vol.45, Is.8. - P.439-447.
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Tutubalina E, Alimova I, Solovyev V., Biomedical entities impact on rating prediction for psychiatric drugs//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2019. - Vol.11832 LNCS, Is.. - P.97-104.
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Alimova I, Tutubalina E., Comparative analysis of context representation models in the relation extraction task from biomedical texts//CEUR Workshop Proceedings. - 2019. - Vol.2525, Is.. - .
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Rusnachenko N, Loukachevitch N, Tutubalina E., Distant supervision for sentiment attitude extraction//International Conference Recent Advances in Natural Language Processing, RANLP. - 2019. - Vol.2019-September, Is.. - P.1022-1030.
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Nikolenko S.I, Tutubalina E, Malykh V, AspeRa: Aspect-based rating prediction model//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2019. - Vol.11438 LNCS, Is.. - P.163-171.
2018
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Alimova I, Tutubalina E., Automated detection of adverse drug reactions from social media posts with machine learning//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2018. - Vol.10716 LNCS, Is.. - P.3-15.
Automated_Detection_of_Adverse_Drug_Reactions_From_Social_Media_Posts_With_Machine_Learning.pdf -
Miftahutdinov Z, Tutubalina E., End-to-end deep framework for disease named entity recognition using social media data//IEEE 30th Jubilee Neumann Colloquium, NC 2017. - 2018. - Vol.2018-January, Is.. - P.47-52.
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Miftahutdinov Z, Tutubalina E., Deep learning for ICD coding: Looking for medical concepts in clinical documents in english and in French//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2018. - Vol.11018 LNCS, Is.. - P.203-215.
- Khasianov A., Alimova I., Marchenko A., Lawyer's Intellectual Tool for Analysis of Legal Documents in Russian//2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE: APPLICATIONS AND INNOVATIONS (IC-AIAI). - 2018. - Vol., Is.. - P.42-46.
- Nugmanov R., Tutubalina E., Miftahutdinov Z., Exploring semantic analysis of biomedical texts for identification of drugs with similar therapeutic effects//EUROPEAN JOURNAL OF CLINICAL INVESTIGATION. - 2018. - Vol.48, Is.. - P.217-217.
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Miftahutdinov Z, Tutubalina E., Leveraging deep neural networks and semantic similarity measures for medical concept normalisation in user reviews//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2018. - Vol.2018-May, Is.17. - P.469-489.
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Tutubalina E, Miftahutdinov Z, Nikolenko S, Medical concept normalization in social media posts with recurrent neural networks//Journal of Biomedical Informatics. - 2018. - Vol.84, Is.. - P.93-102.
- Nugmanov R., Alimova I., Tutubalina E., Detecting adverse drug reactions from user reviews with machine learning//EUROPEAN JOURNAL OF CLINICAL INVESTIGATION. - 2018. - Vol.48, Is.. - P.217-218.
2017
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Tutubalina E, Nikolenko S., Constructing aspect-based sentiment lexicons with topic modeling//Communications in Computer and Information Science. - 2017. - Vol.661, Is.. - P.208-220.
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Tutubalina E, Nikolenko S., Automated prediction of demographic information from medical user reviews//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2017. - Vol.10089 LNAI, Is.. - P.174-184.
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Tutubalina E, Nikolenko S., Demographic prediction based on user reviews about medications//Computacion y Sistemas. - 2017. - Vol.21, Is.2. - P.227-241.
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Miftahutdinov Z.Sh, Tutubalina E.V, Tropsha A.E., Identifying disease-related expressions in reviews using conditional random fields//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2017. - Vol.1, Is.16. - P.155-166.
miftahutdinovzshetal.pdf -
Tutubalina Elena, Nikolenko Sergey. Exploring convolutional neural networks and topic models for user profiling from drug reviews // Multimedia Tools and Applications. — 2017.
exploring_convolutional_neural_4.pdf -
Alimova I., Tutubalina E., Alferova J., Gafiyatullina G. A. Machine Learning Approach to Classification of drug reviews in Russian // Proceedings of Ivannikov ISPRAS Open Conference. - 2017
A_Machine_Learning_Approach_to_Classification_of_Drug_Reviews_in_Russian.pdf -
Miftahutdinov Z, Tutubalina E., KFU at CLEF eHealth 2017 Task 1: ICD-10 coding of English death certificates with recurrent neural networks//CEUR Workshop Proceedings. - 2017. - Vol.1866, Is.. - .
paper_64.pdf -
Tutubalina E.V, Miftahutdinov Z.S, Nugmanov R.I, Using semantic analysis of texts for the identification of drugs with similar therapeutic effects//Russian Chemical Bulletin. - 2017. - Vol.66, Is.11. - P.2180-2189.
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Alimova Ilseyar, Tutubalina Elena, Alferova Julia, A Machine Learning Approach to Classification of Drug Reviews in Russian//2017 IVANNIKOV ISPRAS OPEN CONFERENCE (ISPRAS). - 2017. - Vol., Is.. - P.64-69.
F_A_Machine_Learning_Approach_to_Classification_of_Drug_Reviews_in_Russian.pdf -
Miftahutdinov Zulfat, Tutubalina Elena, End-to-End Deep Framework for Disease Named Entity Recognition Using Social Media Data//2017 IEEE 30TH NEUMANN COLLOQUIUM (NC). - 2017. - Vol., Is.. - P.47-52.
end_end_deep.pdf - Schmitt Charles, Cox Steven, Christopherson Laura, Mining protein interactions from biomedical literature using semantic similarity//ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY. - 2017. - Vol.253, Is.. - .
- Tutubalina Elena, Nikolenko Sergey, Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews//JOURNAL OF HEALTHCARE ENGINEERING. - 2017. - Vol., Is.. - Art. №9451342.
2016
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Tutubalina E., Mining complaints to improve a product: A study about problem phrase extraction from user reviews//WSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining. - 2016. - Vol., Is.. - P.699-.
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Tutubalina E.V, Braslavski P.I., Multiple features for multiword extraction: A learning-to-rank approach//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2016. - Vol., Is.. - P.782-791.
F_tutubalinaev_dialog2016.pdf -
Tutubalina E., Identifying product failures from reviews in noisy data by distant supervision//Communications in Computer and Information Science. - 2016. - Vol.649, Is.. - P.142-156.
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Tutubalina E., A sentiment-aware topic model for extracting failures from product reviews//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2016. - Vol.9924, Is.. - P.37-45.
2015
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Tutubalina E.V, Zagulova M.A, Ivanov V.V, A supervised approach for SentiRuEval task on sentiment analysis of tweets about telecom and financial companies//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2015. - Vol.2, Is.14. - P.65-75.
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Tutubalina E., Dependency-based problem phrase extraction from user reviews of products//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2015. - Vol.9302, Is.. - P.199-206.
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Tutubalina E., Target-based topic model for problem phrase extraction//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2015. - Vol.9022, Is.. - P.271-277.
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Tutubalina E, Nikolenko S., Inferring sentiment-based priors in topic models//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2015. - Vol.9414, Is.. - P.92-104.
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Loukachevitch N.V, Blinov P.D, Kotelnikov E.V, SentiRuEval: Testing Object-oriented sentiment analysis systems in Russian//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2015. - Vol.2, Is.14. - P.3-15.
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Ivanov V.V, Tutubalina E.V, Mingazov N.R, Extracting aspects, sentiment and categories of aspects in user reviews about restaurants and cars//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2015. - Vol.2, Is.14. - P.22-33.
2014
| Work address: | 1/29 Lobachevskogo Str., Kazan, Building #16 (Faculty of Chemistry) |
| Office number: | 505 |
| E-mail: | ElVTutubalina@kpfu.ru |
| VK: | https://vk.com/id2148609 |
| Google scholar: | https://scholar.google.ru/citations?user=npM9yekAAAAJ |
| Experience: |
| Scientific and pedagogical experience: |
| General experience: |
| Experience in KFU: |
