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Child-Sum EATree-LSTMs: enhanced attentive Child-Sum Tree-LSTMs for biomedical event extraction
BackgroundTree-structured neural networks have shown promise in extracting lexical representations of sentence syntactic structures, particularly in...
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Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT
BackgroundThe abundance of biomedical text data coupled with advances in natural language processing (NLP) is resulting in novel biomedical NLP...
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Automatic extraction of ranked SNP-phenotype associations from text using a BERT-LSTM-based method
Extraction of associations of singular nucleotide polymorphism (SNP) and phenotypes from biomedical literature is a vital task in BioNLP. Recently,...
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Comparing neural models for nested and overlap** biomedical event detection
BackgroundNested and overlap** events are particularly frequent and informative structures in biomedical event extraction. However,...
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C-Norm: a neural approach to few-shot entity normalization
BackgroundEntity normalization is an important information extraction task which has gained renewed attention in the last decade, particularly in the...
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A biomedical event extraction method based on fine-grained and attention mechanism
BackgroundBiomedical event extraction is a fundamental task in biomedical text mining, which provides inspiration for medicine research and disease...
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Parallel sequence tagging for concept recognition
BackgroundNamed Entity Recognition (NER) and Normalisation (NEN) are core components of any text-mining system for biomedical texts. In a traditional...
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An analysis of entity normalization evaluation biases in specialized domains
BackgroundEntity normalization is an important information extraction task which has recently gained attention, particularly in the...
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Bio-semantic relation extraction with attention-based external knowledge reinforcement
BackgroundSemantic resources such as knowledge bases contains high-quality-structured knowledge and therefore require significant effort from domain...
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A Text Mining Protocol for Mining Biological Pathways and Regulatory Networks from Biomedical Literature
A biological pathway or regulatory network is a collection of molecular regulators which can activate the changes in cellular processes leading to an...
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Temporal Relation Prediction from Electronic Health Records Using Graph Neural Networks and Transformers Embeddings
Temporal relations extraction is a key factor in many Natural Language Processing (NLP) tasks and, particularly, in clinical text mining. Previous...
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Multiple-level biomedical event trigger recognition with transfer learning
BackgroundAutomatic extraction of biomedical events from literature is an important task in the understanding biological systems, allowing for faster...
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Relation extraction between bacteria and biotopes from biomedical texts with attention mechanisms and domain-specific contextual representations
BackgroundThe Bacteria Biotope (BB) task is a biomedical relation extraction (RE) that aims to study the interaction between bacteria and their...
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A Hybrid Protocol for Identifying Comorbidity-Based Potential Drugs for COVID-19 Using Biomedical Literature Mining, Network Analysis, and Deep Learning
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has spread on an unprecedented scale around...
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A transfer learning model with multi-source domains for biomedical event trigger extraction
BackgroundAutomatic extraction of biomedical events from literature, that allows for faster update of the latest discoveries automatically, is a...
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Bidirectional long short-term memory with CRF for detecting biomedical event trigger in FastText semantic space
BackgroundIn biomedical information extraction, event extraction plays a crucial role. Biological events are used to describe the dynamic effects or...
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Refining electronic medical records representation in manifold subspace
BackgroundElectronic medical records (EMR) contain detailed information about patient health. Develo** an effective representation model is of...
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Biomedical event extraction based on GRU integrating attention mechanism
BackgroundBiomedical event extraction is a crucial task in biomedical text mining. As the primary forum for international evaluation of different...
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Biomedical document triage using a hierarchical attention-based capsule network
BackgroundBiomedical document triage is the foundation of biomedical information extraction, which is important to precision medicine. Recently, some...
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Literature mining for context-specific molecular relations using multimodal representations (COMMODAR)
AbstractBiological contextual information helps understand various phenomena occurring in the biological systems consisting of complex molecular...
