[HTML][HTML] The 2011–2020 trends of data-driven approaches in medical informatics for active pharmacovigilance
H Shin, J Cha, C Lee, H Song, H Jeong, JY Kim… - Applied Sciences, 2021 - mdpi.com
Pharmacovigilance, the scientific discipline pertaining to drug safety, has been studied
extensively and is progressing continuously. In this field, medical informatics techniques and …
extensively and is progressing continuously. In this field, medical informatics techniques and …
Linking biochemical pathways and networks to adverse drug reactions
There is growing interest in investigating the biochemical pathways involved in cellular
responses to drugs. Here we propose new methods to explore the relationships between …
responses to drugs. Here we propose new methods to explore the relationships between …
Information on adverse drug reactions—proof of principle for a structured database that allows customization of drug information
MKP Kusch, A Zien, C Hachenberg, WE Haefeli… - International Journal of …, 2020 - Elsevier
Background The drug information most commonly requested by patients is to learn more
about potential adverse drug reactions (ADRs) of their drugs. Such information should be …
about potential adverse drug reactions (ADRs) of their drugs. Such information should be …
Machine learning-based methods and novel data models to predict adverse drug reaction
Predicting adverse drug reactions (ADRs) plays a critical role in developing new drugs and
preventing adverse reactions during the treatment of existing drugs. However, with the rapid …
preventing adverse reactions during the treatment of existing drugs. However, with the rapid …
[HTML][HTML] Formalizing MedDRA to support semantic reasoning on adverse drug reaction terms
C Bousquet, É Sadou, J Souvignet, MC Jaulent… - Journal of biomedical …, 2014 - Elsevier
Although MedDRA has obvious advantages over previous terminologies for coding adverse
drug reactions and discovering potential signals using data mining techniques, its …
drug reactions and discovering potential signals using data mining techniques, its …
[HTML][HTML] Mining multi-item drug adverse effect associations in spontaneous reporting systems
Background Multi-item adverse drug event (ADE) associations are associations relating
multiple drugs to possibly multiple adverse events. The current standard in …
multiple drugs to possibly multiple adverse events. The current standard in …
[HTML][HTML] PHARMIP: An insilico method to predict genetics that underpin adverse drug reactions
Pharmacovigilance is the pharmacological science that focuses on the safe and appropriate
use of drugs. Variability in response to drug therapy in both terms of safety and efficacy is …
use of drugs. Variability in response to drug therapy in both terms of safety and efficacy is …
mtADENet: A novel interpretable method integrating multiple types of network-based inference approaches for prediction of adverse drug events
Z Yu, Z Wu, M Zhou, L Chen, W Li, G Liu… - Computers in Biology and …, 2024 - Elsevier
Identification of adverse drug events (ADEs) is crucial to reduce human health risks and
accelerate drug safety assessment. ADEs are mainly caused by unintended interactions with …
accelerate drug safety assessment. ADEs are mainly caused by unintended interactions with …
[HTML][HTML] Computational advances in drug safety: systematic and mapping review of knowledge engineering based approaches
Drug Safety (DS) is a domain with significant public health and social impact. Knowledge
Engineering (KE) is the Computer Science discipline elaborating on methods and tools for …
Engineering (KE) is the Computer Science discipline elaborating on methods and tools for …
[HTML][HTML] ADEpedia 2.0: integration of normalized adverse drug events (ADEs) knowledge from the UMLS
Abstract A standardized Adverse Drug Events (ADEs) knowledge base that encodes known
ADE knowledge can be very useful in improving ADE detection for drug safety surveillance …
ADE knowledge can be very useful in improving ADE detection for drug safety surveillance …