no code implementations • CLIB 2020 • Ilseyar Alimova, Elena Tutubalina, Alexander Kirillovich
As source data for transfer learning, we experimented with the full version of FrameNet and the reduced dataset with a smaller number of semantic roles identical to FrameBank.
no code implementations • SMM4H (COLING) 2020 • Ari Klein, Ilseyar Alimova, Ivan Flores, Arjun Magge, Zulfat Miftahutdinov, Anne-Lyse Minard, Karen O’Connor, Abeed Sarker, Elena Tutubalina, Davy Weissenbacher, Graciela Gonzalez-Hernandez
The vast amount of data on social media presents significant opportunities and challenges for utilizing it as a resource for health informatics.
no code implementations • NAACL (SMM4H) 2021 • Arjun Magge, Ari Klein, Antonio Miranda-Escalada, Mohammed Ali Al-Garadi, Ilseyar Alimova, Zulfat Miftahutdinov, Eulalia Farre, Salvador Lima López, Ivan Flores, Karen O’Connor, Davy Weissenbacher, Elena Tutubalina, Abeed Sarker, Juan Banda, Martin Krallinger, Graciela Gonzalez-Hernandez
The global growth of social media usage over the past decade has opened research avenues for mining health related information that can ultimately be used to improve public health.
1 code implementation • 26 Mar 2024 • Veronika Grigoreva, Anastasiia Ivanova, Ilseyar Alimova, Ekaterina Artemova
To illustrate the dataset's purpose, we conduct a diagnostic evaluation of state-of-the-art or near-state-of-the-art LLMs and discuss the LLMs' predisposition to social biases.
no code implementations • 14 Nov 2023 • Konstantin Yakovlev, Gregory Polyakov, Ilseyar Alimova, Alexander Podolskiy, Andrey Bout, Sergey Nikolenko, Irina Piontkovskaya
A recent trend in multimodal retrieval is related to postprocessing test set results via the dual-softmax loss (DSL).
no code implementations • 24 Nov 2021 • Ilseyar Alimova, Elena Tutubalina
Automatic monitoring of adverse drug events (ADEs) or reactions (ADRs) is currently receiving significant attention from the biomedical community.
1 code implementation • 7 Apr 2020 • Elena Tutubalina, Ilseyar Alimova, Zulfat Miftahutdinov, Andrey Sakhovskiy, Valentin Malykh, Sergey Nikolenko
For the sentence classification task, our model achieves the macro F1 score of 68. 82% gaining 7. 47% over the score of BERT model trained on Russian data.
no code implementations • WS 2019 • Ilseyar Alimova, Elena Tutubalina
This paper presents our experimental work on exploring the potential of neural network models developed for aspect-based sentiment analysis for entity-level adverse drug reaction (ADR) classification.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • WS 2019 • Zulfat Miftahutdinov, Ilseyar Alimova, Elena Tutubalina
The end-to-end model based on BERT for ADR normalization ranked first at the SMM4H 2019 Task 3 and obtained a relaxed F1 of 43. 2{\%}.
no code implementations • ACL 2019 • Ilseyar Alimova, Elena Tutubalina
Detection of adverse drug reactions in postapproval periods is a crucial challenge for pharmacology.