AIMC Topic: Drug Interactions

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Identification of adverse drug-drug interactions through causal association rule discovery from spontaneous adverse event reports.

Artificial intelligence in medicine
OBJECTIVE: Drug-drug interaction (DDI) is of serious concern, causing over 30% of all adverse drug reactions and resulting in significant morbidity and mortality. Early discovery of adverse DDI is critical to prevent patient harm. Spontaneous reporti...

A Topic-modeling Based Framework for Drug-drug Interaction Classification from Biomedical Text.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Classification of drug-drug interaction (DDI) from medical literatures is significant in preventing medication-related errors. Most of the existing machine learning approaches are based on supervised learning methods. However, the dynamic nature of d...

Multichannel Convolutional Neural Network for Biological Relation Extraction.

BioMed research international
The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are suscep...

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 ...

Introducing the Big Knowledge to Use (BK2U) challenge.

Annals of the New York Academy of Sciences
The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK),...

Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression.

Journal of chemical information and modeling
Activity cliffs (ACs) are formed by structurally similar compounds with large differences in activity. Accordingly, ACs are of high interest for the exploration of structure-activity relationships (SARs). ACs reveal small chemical modifications that ...

Persisting Hypocalcemia After Surgical Parathyroidectomy: The Differential Effectiveness of Calcium Citrate Versus Calcium Carbonate With Acid Suppression.

The American journal of the medical sciences
The effectiveness of oral calcium (Ca) may be contingent on a patient׳s factors beyond compliance, such as proton-pump inhibitor use and the choice of calcium supplements. A 32-year-old Hispanic male with end-stage renal disease on peritoneal dialysi...

Extracting drug-enzyme relation from literature as evidence for drug drug interaction.

Journal of biomedical semantics
BACKGROUND: Information about drug-drug interactions (DDIs) is crucial for computational applications such as pharmacovigilance and drug repurposing. However, existing sources of DDIs have the problems of low coverage, low accuracy and low agreement....

Drug-Drug Interaction Extraction via Convolutional Neural Networks.

Computational and mathematical methods in medicine
Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a lar...

A randomized-controlled clinical trial investigating the effect of omega-3 fatty acids and vitamin E co-supplementation on markers of insulin metabolism and lipid profiles in gestational diabetes.

Journal of clinical lipidology
BACKGROUND: Limited data are available that evaluated the effects of combined omega-3 fatty acids and vitamin E supplementation on glucose homeostasis parameters and lipid concentrations in gestational diabetes (GDM).