Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-...
Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data
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Publisher
England: BioMed Central Ltd
Journal title
Language
English
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Publisher
England: BioMed Central Ltd
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Scope and Contents
Contents
Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influ...
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Full title
Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data
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TN_cdi_doaj_primary_oai_doaj_org_article_90c753918c9f424a824506ed900513e9
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_90c753918c9f424a824506ed900513e9
Other Identifiers
ISSN
1472-6947
E-ISSN
1472-6947
DOI
10.1186/s12911-024-02521-3
