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dc.contributor.authorLim, Soo-Jin-
dc.contributor.authorLee, Zoonky-
dc.contributor.authorKwon, Lee-Nam-
dc.contributor.authorChun, Hong-Woo-
dc.date.accessioned2024-01-19T14:00:39Z-
dc.date.available2024-01-19T14:00:39Z-
dc.date.created2022-04-05-
dc.date.issued2021-09-
dc.identifier.issn1661-7827-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/116481-
dc.description.abstractDementia is a cognitive impairment that poses a global threat. Current dementia treatments slow the progression of the disease. The timing of starting such treatment markedly affects the effectiveness of the treatment. Some experts mentioned that the optimal timing for starting the currently available treatment in order to delay progression to dementia is the mild cognitive impairment stage, which is the prior stage of dementia. However, medical records are typically only available at a later stage, i.e., from the early or middle stage of dementia. In order to address this limitation, this study developed a model using national health information data from 5 years prior, to predict dementia development 5 years in the future. The Senior Cohort Database, comprising 550,000 samples, were used for model development. The F-measure of the model predicting dementia development after a 5-year incubation period was 77.38%. Models for a 1- and 3-year incubation period were also developed for comparative analysis of dementia risk factors. The three models had some risk factors in common, but also had unique risk factors, depending on the stage. For the common risk factors, a difference in disease severity was confirmed. These findings indicate that the diagnostic criteria and treatment strategy for dementia should differ depending on the timing. Furthermore, since the results of this study present new dementia risk factors that have not been reported previously, this study may also contribute to identification of new dementia risk factors.-
dc.languageEnglish-
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)-
dc.titleMedical Health Records-Based Mild Cognitive Impairment (MCI) Prediction for Effective Dementia Care-
dc.typeArticle-
dc.identifier.doi10.3390/ijerph18179223-
dc.description.journalClass1-
dc.identifier.bibliographicCitationInternational Journal of Environmental Research and Public Health, v.18, no.17-
dc.citation.titleInternational Journal of Environmental Research and Public Health-
dc.citation.volume18-
dc.citation.number17-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000694180900001-
dc.identifier.scopusid2-s2.0-85114193579-
dc.relation.journalWebOfScienceCategoryEnvironmental Sciences-
dc.relation.journalWebOfScienceCategoryPublic, Environmental & Occupational Health-
dc.relation.journalResearchAreaEnvironmental Sciences & Ecology-
dc.relation.journalResearchAreaPublic, Environmental & Occupational Health-
dc.type.docTypeArticle-
dc.subject.keywordPlusSUPPORT VECTOR MACHINE-
dc.subject.keywordPlusINSURANCE SERVICE-
dc.subject.keywordPlusPREVENTION-
dc.subject.keywordPlusDATABASE-
dc.subject.keywordPlusDISEASE-
dc.subject.keywordAuthordementia early prediction-
dc.subject.keywordAuthormachine learning-
dc.subject.keywordAuthormedical records-
dc.subject.keywordAuthormild cognitive impairment prediction-
dc.subject.keywordAuthorsenior cohort-
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KIST Article > 2021
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