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Healthcare platform and big data analysis based personal fitness healthcare service model

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dc.contributor.authorWen, Long Ri-
dc.contributor.authorYang, Seung Min-
dc.contributor.authorLee, Byung Mun-
dc.date.available2020-02-28T03:43:13Z-
dc.date.created2020-02-12-
dc.date.issued2016-10-
dc.identifier.issn2233-7849-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/8773-
dc.description.abstractHuman beings are living longer these days thanks to developments in medical technology and health care services, and accordingly, the global population is rapidly aging. The increasing aging generation is causing unexpected social problems, one of the most critical of which is government health care costs. Personal gene analysis results and record-based personal health care ICT services should predict and prevent personal diseases while improving wellness. Technically, gene sequencing technology development not only reduces the time to decode genetic information but also decreases the cost. Various disease-related gene mutations have been found, and gene sequencing service is a new paradigm in personal health care. In socioeconomic terms, the proposed service model not only accurately diagnoses diseases to provide effective health care but also reduces government health care costs while promoting personal well-being. In this paper, we propose a PGAR (personal gene analysis record) and PHR (personal health care record)-based personal health care service. We implemented this big data analysis-based health care platform for more accurate disease prediction and prevention. When the personal smart health care ICT service is used, it significantly reduces personal health care costs in hospitals. © 2016 SERSC.-
dc.language영어-
dc.language.isoen-
dc.publisherScience and Engineering Research Support Society-
dc.relation.isPartOfInternational Journal of Bio-Science and Bio-Technology-
dc.titleHealthcare platform and big data analysis based personal fitness healthcare service model-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.doi10.14257/ijbsbt.2016.8.5.11-
dc.identifier.bibliographicCitationInternational Journal of Bio-Science and Bio-Technology, v.8, no.5, pp.115 - 128-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-84994314275-
dc.citation.endPage128-
dc.citation.startPage115-
dc.citation.titleInternational Journal of Bio-Science and Bio-Technology-
dc.citation.volume8-
dc.citation.number5-
dc.contributor.affiliatedAuthorLee, Byung Mun-
dc.type.docTypeArticle-
dc.subject.keywordAuthorBig data-
dc.subject.keywordAuthorCohort DB-
dc.subject.keywordAuthorICT-
dc.subject.keywordAuthorPGAR-
dc.subject.keywordAuthorPHR-
dc.subject.keywordAuthorU-Health-
dc.description.journalRegisteredClassscopus-
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College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))
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