Using random forest to identify longitudinal predictors of health in a 30-year cohort study

Due to the wealth of exposome data from longitudinal cohort studies that is currently available, the need for methods to adequately analyze these data is growing. We propose an approach in which machine learning is used to identify longitudinal exposome-related predictors of health, and illustrate i...

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Detalles Bibliográficos
Autores principales: Loef, Bette, Wong, Albert, Janssen, Nicole A. H., Strak, Maciek, Hoekstra, Jurriaan, Picavet, H. Susan J., Boshuizen, H. C. Hendriek, Verschuren, W. M. Monique, Herber, Gerrie-Cor M.
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/PMC9209521/
https://www.ncbi.nlm.nih.gov/pubmed/35725920
http://dx.doi.org/10.1038/s41598-022-14632-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209521/
https://www.ncbi.nlm.nih.gov/pubmed/35725920
http://dx.doi.org/10.1038/s41598-022-14632-w

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