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Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study
We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were built using gradient boosting decision trees...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626442/ https://www.ncbi.nlm.nih.gov/pubmed/34837000 http://dx.doi.org/10.1038/s41598-021-02476-9 |