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Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study (vol 21, e11029, 2019)

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dc.contributor.authorCho, Chul Hyun-
dc.contributor.authorLee, Taek-
dc.contributor.authorKim, Min-Gwan-
dc.contributor.authorIn, Hoh Peter-
dc.contributor.authorKim, Leen-
dc.contributor.authorLee, Heon-Jeong-
dc.date.available2020-11-02T06:29:34Z-
dc.date.issued2019-10-
dc.identifier.issn1439-4456-
dc.identifier.issn1438-8871-
dc.identifier.urihttps://scholarworks.korea.ac.kr/kumedicine/handle/2020.sw.kumedicine/1521-
dc.description.abstract[No abstract available]-
dc.language영어-
dc.language.isoENG-
dc.publisherJournal of medical Internet Research-
dc.titleMood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study (vol 21, e11029, 2019)-
dc.typeArticle-
dc.publisher.location캐나다-
dc.identifier.doi10.2196/15966-
dc.identifier.scopusid2-s2.0-85072930607-
dc.identifier.wosid000488775800001-
dc.identifier.bibliographicCitationJournal of Medical Internet Research, v.21, no.10, pp e15966-
dc.citation.titleJournal of Medical Internet Research-
dc.citation.volume21-
dc.citation.number10-
dc.citation.startPagee15966-
dc.type.docTypeCorrection-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaHealth Care Sciences & Services-
dc.relation.journalResearchAreaMedical Informatics-
dc.relation.journalWebOfScienceCategoryHealth Care Sciences & Services-
dc.relation.journalWebOfScienceCategoryMedical Informatics-
dc.subject.keywordAuthormood disorder-
dc.subject.keywordAuthorcircadian rhythm-
dc.subject.keywordAuthorprediction-
dc.subject.keywordAuthormachine learning-
dc.subject.keywordAuthordigital phenotype-
dc.subject.keywordAuthorwearable device-
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