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SCI Abstract
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An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser Ontology
Automatic disease progression prediction models require large amounts of training data, which are seldom available, especi...
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Annotation of epilepsy clinic letters for natural language processing
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MeSH2Matrix: combining MeSH keywords and machine learning for biomedical relation classification based on PubMed
Biomedical relation classification has been significantly improved by the application of advanced machine learning techniq...
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Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)
Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food...
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Explanatory argumentation in natural language for correct and incorrect medical diagnoses
A huge amount of research is carried out nowadays in Artificial Intelligence to propose automated ways to analyse medical ...
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Optimized continuous homecare provisioning through distributed data-driven semantic services and cross-organizational workflows
In healthcare, an increasing collaboration can be noticed between different caregivers, especially considering the shift t...
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Multi-task transfer learning for the prediction of entity modifiers in clinical text: application to opioid use disorder case detection
The semantics of entities extracted from a clinical text can be dramatically altered by modifiers, including entity negati...
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Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis
The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. T...
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The use of foundational ontologies in biomedical research
The FAIR principles recommend the use of controlled vocabularies, such as ontologies, to define data and metadata concepts...
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Enriching the FIDEO ontology with food-drug interactions from online knowledge sources
The increasing number of articles on adverse interactions that may occur when specific foods are consumed with certain dru...
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BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs
Knowledge graphs (KGs) are an important tool for representing complex relationships between entities in the biomedical dom...
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Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases
Healthcare data and the knowledge gleaned from it play a key role in improving the health of current and future patients. ...
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Impact of COVID-19 research: a study on predicting influential scholarly documents using machine learning and a domain-independent knowledge graph
Multiple studies have investigated bibliometric features and uncategorized scholarly documents for the influential scholar...
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Data management plans as linked open data: exploiting ARGOS FAIR and machine actionable outputs in the OpenAIRE research graph
Open Science Graphs (OSGs) are scientific knowledge graphs representing different entities of the research lifecycle (e.g....
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Context-based refinement of mappings in evolving life science ontologies
Biomedical computational systems benefit from ontologies and their associated mappings. Indeed, aligned ontologies in life...
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Analysis and implementation of the DynDiff tool when comparing versions of ontology
Ontologies play a key role in the management of medical knowledge because they have the properties to support a wide range...
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Development and validation of the early warning system scores ontology
Clinical early warning scoring systems, have improved patient outcomes in a range of specializations and global contexts. ...
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Automatic transparency evaluation for open knowledge extraction systems
This paper proposes Cyrus, a new transparency evaluation framework, for Open Knowledge Extraction (OKE) systems. Cyrus is ...
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Automatic classification of experimental models in biomedical literature to support searching for alternative methods to animal experiments
Current animal protection laws require replacement of animal experiments with alternative methods, whenever such methods a...
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Multi-domain knowledge graph embeddings for gene-disease association prediction
Predicting gene-disease associations typically requires exploring diverse sources of information as well as sophisticated ...
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An extension of the BioAssay Ontology to include pharmacokinetic/pharmacodynamic terminology for the enrichment of scientific workflows
With the capacity to produce and record data electronically, Scientific research and the data associated with it have grow...
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Improving the classification of cardinality phenotypes using collections
Phenotypes are observable characteristics of an organism and they can be highly variable. Information about phenotypes is ...
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Semantically enabling clinical decision support recommendations
Clinical decision support systems have been widely deployed to guide healthcare decisions on patient diagnosis, treatment ...
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FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards
The current rise of Open Science and Reproducibility in the Life Sciences requires the creation of rich, machine-actionabl...
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Features of a FAIR vocabulary
The Findable, Accessible, Interoperable and Reusable(FAIR) Principles explicitly require the use of FAIR vocabularies, but...
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Multiple sampling schemes and deep learning improve active learning performance in drug-drug interaction information retrieval analysis from the literature
Drug-drug interaction (DDI) information retrieval (IR) is an important natural language process (NLP) task from the PubMed...
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Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets
The majority of available datasets in open government data are statistical. They are widely published by various governmen...
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The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond
Evaluating the impact of environmental exposures on organism health is a key goal of modern biomedicine and is critically ...
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MedLexSp – a medical lexicon for Spanish medical natural language processing
Medical lexicons enable the natural language processing (NLP) of health texts. Lexicons gather terms and concepts from the...
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Classifying literature mentions of biological pathogens as experimentally studied using natural language processing
Information pertaining to mechanisms, management and treatment of disease-causing pathogens including viruses and bacteria...
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