Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovas...
Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
This study looked at novel data sources for cardiovascular risk prediction including detailed lifestyle questionnaire and continuous blood pressure monitoring, using ensemble machine learning algorithms (MLAs). The reference conventional risk score compared against was the Framingham Risk Score (FRS). The outcome variables were low or high risk bas...
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Full title
Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction
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TN_cdi_doaj_primary_oai_doaj_org_article_c03f57a44af540e6b8b5a43bcc0e755a
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c03f57a44af540e6b8b5a43bcc0e755a
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-021-04649-y
