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An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-C…

2020

Background Lifestyle diseases, because of adverse health behavior, are the foremost cause of death worldwide. An eCoach system may encourage individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Such an eCoach system needs to collect and transform distributed heterogenous health and wellness data into meaningful information to train an artificially intelligent health risk prediction model. However, it may produce a data compatibility dilemma. Our proposed eHealth ontology can increase interoperability between different heterogeneous networks, provide situation awareness, help in data integration, and discover…

recommendationDatabases Factual020205 medical informaticsComputer scienceinteroperabilityHealth Informatics02 engineering and technologyOntology (information science)SNOMED CTcomputer.software_genrelcsh:Computer applications to medicine. Medical informaticsProof of Concept Studysensorhealthy lifestyle0202 electrical engineering electronic engineering information engineeringHumansSPARQLontologypropositionRDFsemanticsSemantic Webcomputer.programming_languagegoal settingOriginal PaperSSNInformation retrievalactivityquestionnairelcsh:Public aspects of medicinepersonalizedlcsh:RA1-1270eCoachcomputer.file_formatSemantic reasonerProtégésimulationTelemedicinenutritionautomatedlcsh:R858-859.7eHealth020201 artificial intelligence & image processingCDSScomputerRDF query languageData integrationJournal of Medical Internet Research
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