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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Detalles Bibliográficos
Autores principales: Bonavia, Anthony S., Samuelsen, Abigail, Luthy, Joshua, Halstead, E. Scott
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Immunology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714638/
https://www.ncbi.nlm.nih.gov/pubmed/36466851
http://dx.doi.org/10.3389/fimmu.2022.1007016

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714638/
https://www.ncbi.nlm.nih.gov/pubmed/36466851
http://dx.doi.org/10.3389/fimmu.2022.1007016

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