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- W974571521 abstract "Many studies fail to provide models for 30-day hospital re-admission prediction with satisfactory performance due to high dimensionality and sparsity. Efficient feature selection techniques allow better generalization of predictive models and improved interpretability, which is a very important property for applications in health care. We propose feature selection method that exploits hierarchical domain knowledge together with data. The new method is evaluated on predicting 30-day hospital readmission for pediatric patients from California and provides evidence that a knowledge-based approach outperforms traditional methods and that the newly proposed method is competitive with state-of-the-art methods." @default.
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- W974571521 date "2015-01-01" @default.
- W974571521 modified "2023-09-25" @default.
- W974571521 title "Domain knowledge Based Hierarchical Feature Selection for 30-Day Hospital Readmission Prediction" @default.
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- W974571521 doi "https://doi.org/10.1007/978-3-319-19551-3_11" @default.
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