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Ontology-Aware Biomedical Relation Extraction
Automatically extracting relationships from biomedical texts among multiple sorts of entities is an essential task in biomedical natural language...
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Integrating Ontology-Based Knowledge to Improve Biomedical Multi-Document Summarization Model
Most existing extractive summarization models use the original text’s internal information and calculate each sentence’s importance individually....
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EBOCA: Evidences for BiOmedical Concepts Association Ontology
There is a large number of online documents data sources available nowadays. The lack of structure and the differences between formats are the main...
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IRI_Debug: An Ontology Evaluation Tool
We use ontology to capture the knowledge about domains. There are considerable number of ontologies which have been developed. To develop a new...
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Ontology enrichment from opinions using machine learning algorithms
Systems based on ontologies enable better data exploitation and provide credible and contextualized knowledge. Several sources of knowledge have been...
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CovidO: an ontology for COVID-19 metadata
Ontology is a significant data model for identifying semantic information for Coronavirus disease (COVID-19) discovery. Large-scale biological and...
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Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching
Ontology Matching (OM) plays an important role in many domains such as bioinformatics and the Semantic Web, and its research is becoming...
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Semantic Integration of Heterogeneous Data Sources Using Ontology-Based Domain Knowledge Modeling for Early Detection of COVID-19
The enormous outbreak of biomedical knowledge, the aim of reducing computation and processing costs and the widespread availability of internet...
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Contextual semantic embeddings for ontology subsumption prediction
Automating ontology construction and curation is an important but challenging task in knowledge engineering and artificial intelligence. Prediction...
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Biomedical Knowledge Graph Embeddings with Negative Statements
A knowledge graph is a powerful representation of real-world entities and their relations. The vast majority of these relations are defined as...
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ReOnto: A Neuro-Symbolic Approach for Biomedical Relation Extraction
Relation Extraction (RE) is the task of extracting semantic relationships between entities in a sentence and aligning them to relations defined in a...
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A Graph-Based Ontology Matching Framework
Ontologies are domain-specific metadata that describe relationships between a specific field’s properties, sample data of this field, and properties...
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Knowledge graph enrichment from clinical narratives using NLP, NER, and biomedical ontologies for healthcare applications
Electronic health records (EHR) contain patients’ health information in varied formats such as clinical reports written in natural language, X-rays,...
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A drug prescription recommendation system based on novel DIAKID ontology and extensive semantic rules
According to the World Health Organization (WHO) data from 2000 to 2019, the number of people living with Diabetes Mellitus and Chronic Kidney...
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Building a deep ontology-based herbal medicinal plant search system
Traditional medicine comprises practical experience accumulated over thousands of years. Despite the abundance of published works on medicinal...
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Knowledge-graph-enabled biomedical entity linking: a survey
Biomedical Entity Linking (BM-EL) task, which aims to match biomedical mentions in articles to entities in a certain knowledge base (e.g., the...
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Biomedical Knowledge Representation Learning
As a subject closely related to our life and understanding of the world, biomedicine keeps drawing much attention from researchers in recent years....
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Detection of Gene Ontology Clusters Using Biclustering Algorithms
Detecting essential proteins is important to understand cellular activities. The discovery of important genes across the whole genome is beneficial...
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GenSpecVidOnt: a reference ontology for knowledge based video analytics with multimodal genre detection
Video analytics refers to the process of automatically analysing a video for spatial and temporal events. Effective video analytics require...
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Design of a data storage and retrieval ontology for the efficient integration of information in artificial intelligence systems
This article proposes an innovative approach to designing an ontology for data storage and retrieval, effectively integrating information into...
