Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction

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...

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Detalles Bibliográficos
Autores principales: Huang, Weiting, Ying, Tan Wei, Chin, Woon Loong Calvin, Baskaran, Lohendran, Marcus, Ong Eng Hock, Yeo, Khung Keong, Kiong, Ng See
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776753/
https://www.ncbi.nlm.nih.gov/pubmed/35058500
http://dx.doi.org/10.1038/s41598-021-04649-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776753/
https://www.ncbi.nlm.nih.gov/pubmed/35058500
http://dx.doi.org/10.1038/s41598-021-04649-y

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