Artificial intelligence-based pharmacovigilance in the setting of limited resources

L Liang, J Hu, G Sun, N Hong, G Wu, Y He, Y Li, T Hao… - Drug Safety, 2022 - Springer
With the rapid development of artificial intelligence (AI) technologies, and the large amount
of pharmacovigilance-related data stored in an electronic manner, data-driven automatic …

Review of natural language processing in pharmacology

D Trajanov, V Trajkovski, M Dimitrieva, J Dobreva… - Pharmacological …, 2023 - Elsevier
Natural language processing (NLP) is an area of artificial intelligence that applies
information technologies to process the human language, understand it to a certain degree …

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 …

SCAN: A shared causal attention network for adverse drug reactions detection in tweets

H Kayesh, MS Islam, J Wang, R Ohira, Z Wang - Neurocomputing, 2022 - Elsevier
Twitter is a popular social media site on which people post millions of Tweets every day. As
patients often share their experiences with drugs on Twitter, Tweets can also be considered …

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 …

Multi-aspect deep active attention network for healthcare explainable adoption

U Ahmed, JCW Lin, G Srivastava - IEEE Journal of Biomedical …, 2022 - ieeexplore.ieee.org
Depression is a serious illness that significantly affects the lives of those affected. Recent
studies have looked at the possibility of detecting and diagnosing this mental disorder using …

EDBase: Generating a Lexicon Base for Eating Disorders Via Social Media

T Anwar, M Fuller-Tyszkiewicz… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Eating disorders (EDs) are characterised by abnormal eating habits and obsessive thought
about food, weight, shape, and body image. EDs are experienced by a significant portion of …

Artificial neural network (ANN) in drug delivery

F Piroozmand, F Mohammadipanah… - A Handbook of Artificial …, 2023 - Elsevier
Artificial intelligence (AI) tools can improve the drug delivery process from the early stages of
drug formulation to stimulating, predicting, programming, and optimizing drug delivery in …

[PDF][PDF] Utilising consumer reviews for passive surveillance of foodborne illnesses: insights and challenges from the Indian restaurant

A Prabhune, VS Hari, NK Sethiya… - International Journal of …, 2025 - researchgate.net
This study explores the feasibility of leveraging consumer reviews for passive surveillance of
foodborne illnesses, drawing parallels with pharmacovigilance systems. Utilizing a mixed …

Survey of nlp in pharmacology: Methodology, tasks, resources, knowledge, and tools

D Trajanov, V Trajkovski, M Dimitrieva… - arXiv preprint arXiv …, 2022 - repository.ukim.mk
Natural language processing (NLP) is an area of artificial intelligence that applies
information technologies to process the human language, understand it to a certain degree …