The effect of resampling techniques on the performances of machine learning clinical risk prediction models in the setting of severe class imbalance: development and internal validation in a retrospective cohort
Abstract Purpose The availability of population datasets and machine learning techniques heralded a new era of sophisticated prediction models involving a large number of routinely collected variables. However, severe class imbalance in clinical datasets is a major challenge. The aim of this study i...
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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Springer
2024-11-01
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| Col·lecció: | Discover Artificial Intelligence |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1007/s44163-024-00199-0 |
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