AIMC Topic: Polypharmacy

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Exploring polypharmacy with artificial intelligence: data analysis protocol.

BMC medical informatics and decision making
BACKGROUND: Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and s...

Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The identification of drug-drug interactions (DDIs) is important for patient safety; yet, compared to other pharmacovigilance work, a limited amount of research has been conducted in this space. Recent work has successfully applied a method of derivi...

Network-Based Assessment of Adverse Drug Reaction Risk in Polypharmacy Using High-Throughput Screening Data.

International journal of molecular sciences
The risk of adverse drug reactions increases in a polypharmacology setting. High-throughput drug screening with transcriptomics applied to human cells has shown that drugs have effects on several molecular pathways, and these affected pathways may be...

Drug-drug interaction extraction from biomedical texts using long short-term memory network.

Journal of biomedical informatics
The simultaneous administration of multiple drugs increases the probability of interaction among them, as one drug may affect the activities of others. This interaction among drugs may have a positive or negative impact on the therapeutic outcomes. T...

Identifying Drug-Drug Interactions by Data Mining: A Pilot Study of Warfarin-Associated Drug Interactions.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Knowledge about drug-drug interactions commonly arises from preclinical trials, from adverse drug reports, or based on knowledge of mechanisms of action. Our aim was to investigate whether drug-drug interactions were discoverable without ...

Modeling polypharmacy side effects with graph convolutional networks.

Bioinformatics (Oxford, England)
MOTIVATION: The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases or co-existing conditions. However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient. Po...