Results 21 to 30 of about 907,352 (125)

Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs [PDF]

open access: yesarXiv, 2014
Background: Children are frequently prescribed medication off-label, meaning there has not been sufficient testing of the medication to determine its safety or effectiveness. The main reason this safety knowledge is lacking is due to ethical restrictions that prevent children from being included in the majority of clinical trials.
arxiv  

A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels [PDF]

open access: yesarXiv, 2019
Preventable adverse drug reactions as a result of medical errors present a growing concern in modern medicine. As drug-drug interactions (DDIs) may cause adverse reactions, being able to extracting DDIs from drug labels into machine-readable form is an important effort in effectively deploying drug safety information.
arxiv  

HODDI: A Dataset of High-Order Drug-Drug Interactions for Computational Pharmacovigilance [PDF]

open access: yesarXiv
Drug-side effect research is vital for understanding adverse reactions arising in complex multi-drug therapies. However, the scarcity of higher-order datasets that capture the combinatorial effects of multiple drugs severely limits progress in this field. Existing resources such as TWOSIDES primarily focus on pairwise interactions.
arxiv  

Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learning [PDF]

open access: yesarXiv
In clinical treatment, identifying potential adverse reactions of drugs can help assist doctors in making medication decisions. In response to the problems in previous studies that features are high-dimensional and sparse, independent prediction models need to be constructed for each adverse reaction of drugs, and the prediction accuracy is low, this ...
arxiv  

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