Integrated machine learning approaches for flow cytometric quantification of myeloid-derived suppressor cells in acute sepsis

Highly heterogeneous cell populations require multiple flow cytometric markers for appropriate phenotypic characterization. This exponentially increases the complexity of 2D scatter plot analyses and exacerbates human errors due to variations in manual gating of flow data. We describe a semi-automat...

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Principais autores:	Anthony S. Bonavia, Abigail Samuelsen, Joshua Luthy, E. Scott Halstead
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2022-11-01
coleção:	Frontiers in Immunology
Assuntos:	high parameter flow cytometry sepsis - diagnostics clustering analysis clinical immunology myeloid-derived suppressor cells (MDSC)
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fimmu.2022.1007016/full
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