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Equitable machine learning counteracts ancestral bias in precision medicine, improving outcomes for all
Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease [1–8]. Therapeutics and outcomes remain hidden because we lack insights that we could gain from analyzing ancestry-unbiased genomic data. To address th...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Journal Experts
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402189/ https://www.ncbi.nlm.nih.gov/pubmed/37546907 http://dx.doi.org/10.21203/rs.3.rs-3168446/v1 |