Using machine learning to ace cardiovascular risk tests
Cardiovasc Res
.
2020 Dec 1;116(14):2173-2174.
doi: 10.1093/cvr/cvaa305.
Authors
James R Bell
1
,
Gemma A Figtree
2
3
,
Grant R Drummond
1
4
Affiliations
1
Department of Physiology, Anatomy and Microbiology, School of Life Sciences, La Trobe University, Bundoora, Victoria, Australia.
2
Kolling Institute for Medical Research, Royal North Shore Hospital, St Leonards, Sydney, New South Wales, Australia.
3
Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
4
Centre for Cardiovascular Biology and Disease Research, School of Life Sciences, La Trobe University, Bundoora, Victoria, Australia.
PMID:
33125063
DOI:
10.1093/cvr/cvaa305
No abstract available
Publication types
Editorial
Comment
MeSH terms
Calcium
Cardiovascular Diseases* / diagnosis
Cardiovascular Diseases* / epidemiology
Death
Heart Disease Risk Factors
Humans
Machine Learning
Myocardial Infarction*
Prospective Studies
Risk Factors
Substances
Calcium