Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival

BACKGROUND: Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship, and wh...

Descripción completa

Detalles Bibliográficos
Autores principales: Kosyakovsky, Leah B., Somerset, Emily, Rogers, Angela J., Sklar, Michael, Mayers, Jared R., Toma, Augustin, Szekely, Yishay, Soussi, Sabri, Wang, Bo, Fan, Chun-Po S., Baron, Rebecca M., Lawler, Patrick R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9203139/
https://www.ncbi.nlm.nih.gov/pubmed/35710638
http://dx.doi.org/10.1186/s40635-022-00445-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9203139/
https://www.ncbi.nlm.nih.gov/pubmed/35710638
http://dx.doi.org/10.1186/s40635-022-00445-8

Ejemplares similares