Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models
Abstract In view of the growth of clinical risk prediction models using genetic data, there is an increasing need for studies that use appropriate methods to select the optimum number of features from a large number of genetic variants with a high degree of redundancy between features due to linkage...
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| Autores principales: | , , , , , , , , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/ef9896df34ad40f89822e14d6ff1f794 |
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