Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective study

BACKGROUND AND AIMS: We sought to assess the performance of a comprehensive machine learning (ML) risk score integrating circulating biomarkers and computed tomography (CT) measures for the long-term prediction of hard cardiac events in asymptomatic subjects. METHODS: We studied 1069 subjects (age 5...

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Detalhes bibliográficos
Publicado no:Atherosclerosis
Main Authors: Tamarappoo, Balaji K, Lin, Andrew, Commandeur, Frederic, McElhinney, Priscilla A, Cadet, Sebastien, Goeller, Markus, Razipour, Aryabod, Chen, Xi, Gransar, Heidi, Cantu, Stephanie, Miller, Robert JH, Achenbach, Stephan, Friedman, John, Hayes, Sean, Thomson, Louise, Wong, Nathan D, Rozanski, Alan, Slomka, Piotr J, Berman, Daniel S, Dey, Damini
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7856265/
https://ncbi.nlm.nih.gov/pubmed/33239189
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.atherosclerosis.2020.11.008
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