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Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV)
BACKGROUND: Machine learning methods and conventions are increasingly employed for the analysis of large, complex biomedical data sets, including genome-wide association studies (GWAS). Reproducibility of machine learning analyses of GWAS can be hampered by biological and statistical factors, partic...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907739/ https://www.ncbi.nlm.nih.gov/pubmed/29713384 http://dx.doi.org/10.1186/s13040-018-0167-7 |