A comprehensive review of computational methods for drug-drug interaction detection
The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance,
which provides effective and safe co-prescriptions of multiple drugs. Since laboratory …
which provides effective and safe co-prescriptions of multiple drugs. Since laboratory …
Deep learning for drug–drug interaction extraction from the literature: a review
Drug–drug interactions (DDIs) are crucial for drug research and pharmacovigilance. These
interactions may cause adverse drug effects that threaten public health and patient safety …
interactions may cause adverse drug effects that threaten public health and patient safety …
[PDF][PDF] Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013)
I Segura-Bedmar, P Martínez… - … Joint Conference on …, 2013 - aclanthology.org
The DDIExtraction 2013 task concerns the recognition of drugs and extraction of drugdrug
interactions that appear in biomedical literature. We propose two subtasks for the …
interactions that appear in biomedical literature. We propose two subtasks for the …
Drug‐drug interaction extraction via convolutional neural networks
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 …
language processing (NLP) has always attracted great attention. Most state‐of‐the‐art DDI …
[HTML][HTML] Drug-drug interaction extraction from biomedical texts using long short-term memory network
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 …
among them, as one drug may affect the activities of others. This interaction among drugs …
Drug-drug interaction prediction based on knowledge graph embeddings and convolutional-LSTM network
Interference between pharmacological substances can cause serious medical injuries.
Correctly predicting so-called drug-drug interactions (DDI) does not only reduce these cases …
Correctly predicting so-called drug-drug interactions (DDI) does not only reduce these cases …
Drug drug interaction extraction from biomedical literature using syntax convolutional neural network
Motivation: Detecting drug-drug interaction (DDI) has become a vital part of public health
safety. Therefore, using text mining techniques to extract DDIs from biomedical literature has …
safety. Therefore, using text mining techniques to extract DDIs from biomedical literature has …
Drug–drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths
Motivation Adverse events resulting from drug-drug interactions (DDI) pose a serious health
issue. The ability to automatically extract DDIs described in the biomedical literature could …
issue. The ability to automatically extract DDIs described in the biomedical literature could …
Multichannel convolutional neural network for biological relation extraction
The plethora of biomedical relations which are embedded in medical logs (records)
demands researchers' attention. Previous theoretical and practical focuses were restricted …
demands researchers' attention. Previous theoretical and practical focuses were restricted …
[HTML][HTML] A hybrid model based on neural networks for biomedical relation extraction
Biomedical relation extraction can automatically extract high-quality biomedical relations
from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in …
from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in …