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.
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.
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 • 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 • 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 • ACL 2019 • Ilseyar Alimova, Elena Tutubalina
Detection of adverse drug reactions in postapproval periods is a crucial challenge for pharmacology.