Identifying adverse drug reaction entities from social media with adversarial transfer learning model
Identifying adverse drug reaction (ADR) entities from texts is a crucial task for pharmacology,
and it is the basis for the ADR relation extraction task. The publicly available resources on …
and it is the basis for the ADR relation extraction task. The publicly available resources on …
Analysis of the full-size russian corpus of internet drug reviews with complex ner labeling using deep learning neural networks and language models
A Sboev, S Sboeva, I Moloshnikov, A Gryaznov… - Applied Sciences, 2022 - mdpi.com
The paper presents the full-size Russian corpus of Internet users' reviews on medicines with
complex named entity recognition (NER) labeling of pharmaceutically relevant entities. We …
complex named entity recognition (NER) labeling of pharmaceutically relevant entities. We …
An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neural nets
A Sboev, S Sboeva, I Moloshnikov, A Gryaznov… - arXiv preprint arXiv …, 2021 - arxiv.org
We present the full-size Russian complexly NER-labeled corpus of Internet user reviews,
along with an evaluation of accuracy levels reached on this corpus by a set of advanced …
along with an evaluation of accuracy levels reached on this corpus by a set of advanced …
An effective emotional expression and knowledge-enhanced method for detecting adverse drug reactions
Z Li, H Lin, W Zheng - IEEE Access, 2020 - ieeexplore.ieee.org
Discovering more time-effective and a wider range of adverse drug reactions (ADRs) from
social texts related to feelings concerning taking medication has recently received significant …
social texts related to feelings concerning taking medication has recently received significant …
GAR: Graph adversarial representation for adverse drug event detection on Twitter
Adverse drug reaction events have become one of the main causes of patient death. Since
traditional post-marketing surveillance systems based on spontaneous reports have a …
traditional post-marketing surveillance systems based on spontaneous reports have a …
Comment on:“Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts”
Dear Editor, We read with great interest the article by Cocos et al. 1 In it, the authors use one
of the datasets made public by our lab in parallel with a publication in Journal of the …
of the datasets made public by our lab in parallel with a publication in Journal of the …
A neural network algorithm for extracting pharmacological information from russian-language internet reviews on drugs
AG Sboev, SG Sboeva, AV Gryaznov… - Journal of Physics …, 2020 - iopscience.iop.org
The paper presents a neural network algorithm for analyzing online user reviews of drugs.
The algorithm was validated on specially prepared and annotated corpora. The basis of the …
The algorithm was validated on specially prepared and annotated corpora. The basis of the …
[PDF][PDF] Utilizing Word Index Approach with LSTM Architecture for Extracting Adverse Drug Reaction from Medical Reviews
AJ Alshaikhdeeb, YN Cheah - Journal of Advances in Information Technology, 2023 - jait.us
Adverse Drug Reaction (ADR) detection from social reviews refers to the task of exploring
medical online stores and social reviews for extracting any mention of abnormal reactions …
medical online stores and social reviews for extracting any mention of abnormal reactions …
基于Tri-training 的社交媒体药物不良反应实体抽取.
何忠玻， 严馨， 徐广义， 张金鹏… - Journal of Computer …, 2024 - search.ebscohost.com
社交媒体因其数据的实时性, 对其充分利用可以弥补传统医疗文献药物不良反应中实体抽取的
迟滞性问题, 但社交媒体文本面临标注数据成本高, 数据噪声大等问题, 使得模型难以发挥良好的 …
迟滞性问题, 但社交媒体文本面临标注数据成本高, 数据噪声大等问题, 使得模型难以发挥良好的 …
基于图嵌入的社交媒体药物不良反应事件检测方法.
申晨， 林鸿飞 - Journal of Dalian University of Technology …, 2020 - search.ebscohost.com
药物不良反应事件是造成患者发病, 死亡的主要原因之一. 传统的基于患者自发报告系统存在
较为严重的漏报情况, 近年来将推特等社交媒体作为数据来源进行药物不良反应事件检测的研究 …
较为严重的漏报情况, 近年来将推特等社交媒体作为数据来源进行药物不良反应事件检测的研究 …