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Prediction of fall events during admission using eXtreme gradient boosting: a comparative validation study
As the performance of current fall risk assessment tools is limited, clinicians face significant challenges in identifying patients at risk of falling. This study proposes an automatic fall risk prediction model based on eXtreme gradient boosting (XGB), using a data-driven approach to the standardiz...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544690/ https://www.ncbi.nlm.nih.gov/pubmed/33033326 http://dx.doi.org/10.1038/s41598-020-73776-9 |