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Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa
BACKGROUND: Selecting the optimal combination of HIV drugs for an individual in resource-limited settings is challenging because of the limited availability of drugs and genotyping. OBJECTIVE: The evaluation as a potential treatment support tool of computational models that predict response to thera...
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| Publicado no: | South Afr J HIV Med |
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| Main Authors: | , , , , , , , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
AOSIS
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5843195/ https://ncbi.nlm.nih.gov/pubmed/29568609 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4102/sajhivmed.v17i1.450 |
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