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Accounting for clustering in automated variable selection using hospital data: a comparison of different LASSO approaches
BACKGROUND: Automated feature selection methods such as the Least Absolute Shrinkage and Selection Operator (LASSO) have recently gained importance in the prediction of quality-related outcomes as well as the risk-adjustment of quality indicators in healthcare. The methods that have been used so far...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675967/ https://www.ncbi.nlm.nih.gov/pubmed/38007454 http://dx.doi.org/10.1186/s12874-023-02081-6 |