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An application based on bioinformatics and machine learning for risk prediction of sepsis at first clinical presentation using transcriptomic data
Background: Linking genotypic changes to phenotypic traits based on machine learning methods has various challenges. In this study, we developed a workflow based on bioinformatics and machine learning methods using transcriptomic data for sepsis obtained at the first clinical presentation for predic...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490444/ https://www.ncbi.nlm.nih.gov/pubmed/36159979 http://dx.doi.org/10.3389/fgene.2022.979529 |