AIMC Topic: Biological Ontologies
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An Ontology-Independent Representation Learning for Similar Disease Detection Based on Multi-Layer Similarity Network.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2021
To identify similar diseases has significant implications for revealing the etiology and pathogenesis of diseases and further research in the domain of biomedicine. Currently, most methods for the measurement of disease similarity utilize either asso...
Ontological representation, classification and data-driven computing of phenotypes.
Journal of biomedical semantics
Dec 21, 2020
BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological studies. The development of computable...
Outlier concepts auditing methodology for a large family of biomedical ontologies.
BMC medical informatics and decision making
Dec 15, 2020
BACKGROUND: Summarization networks are compact summaries of ontologies. The "Big Picture" view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concepts. For ontologies that have ...
Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies.
BMC medical informatics and decision making
Dec 15, 2020
BACKGROUND: Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. W...
Analysis of readability and structural accuracy in SNOMED CT.
BMC medical informatics and decision making
Dec 15, 2020
BACKGROUND: The increasing adoption of ontologies in biomedical research and the growing number of ontologies available have made it necessary to assure the quality of these resources. Most of the well-established ontologies, such as the Gene Ontolog...
Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry.
BMC medical informatics and decision making
Dec 15, 2020
BACKGROUND: The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. a...
Quality assurance and enrichment of biological and biomedical ontologies and terminologies.
BMC medical informatics and decision making
Dec 15, 2020
Biological and biomedical ontologies and terminologies are used to organize and store various domain-specific knowledge to provide standardization of terminology usage and to improve interoperability. The growing number of such ontologies and termino...
KGen: a knowledge graph generator from biomedical scientific literature.
BMC medical informatics and decision making
Dec 14, 2020
BACKGROUND: Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new knowledge requires computational ...
COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology.
JMIR public health and surveillance
Nov 17, 2020
BACKGROUND: Creating an ontology for COVID-19 surveillance should help ensure transparency and consistency. Ontologies formalize conceptualizations at either the domain or application level. Application ontologies cross domains and are specified thro...
Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies.
Journal of biomedical semantics
Nov 16, 2020
BACKGROUND: Free-text descriptions in electronic health records (EHRs) can be of interest for clinical research and care optimization. However, free text cannot be readily interpreted by a computer and, therefore, has limited value. Natural Language ...
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