Classification of COVID-19 Patients into Clinically Relevant Subsets by a Novel Machine Learning Pipeline Using Transcriptomic Features

The persistent impact of the COVID-19 pandemic and heterogeneity in disease manifestations point to a need for innovative approaches to identify drivers of immune pathology and predict whether infected patients will present with mild/moderate or severe disease. We have developed a novel iterative ma...

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Detalles Bibliográficos
Autores principales: Daamen, Andrea R., Bachali, Prathyusha, Grammer, Amrie C., Lipsky, Peter E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002748/
https://www.ncbi.nlm.nih.gov/pubmed/36902333
http://dx.doi.org/10.3390/ijms24054905

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002748/
https://www.ncbi.nlm.nih.gov/pubmed/36902333
http://dx.doi.org/10.3390/ijms24054905

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