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Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models
BACKGROUND: Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminatory accuracy (0.53–0.64). Machine learning (ML) of...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6585114/ https://www.ncbi.nlm.nih.gov/pubmed/31221197 http://dx.doi.org/10.1186/s13058-019-1158-4 |