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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...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| 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 |