Six clinical phenotypes with prognostic implications were identified by unsupervised machine learning in children and adolescents with SARS-CoV-2 infection: results from a German nationwide registry

Abstract Objective Phenotypes are important for patient classification, disease prognostication, and treatment customization. We aimed to identify distinct clinical phenotypes of children and adolescents hospitalized with SARS-CoV-2 infection, and to evaluate their prognostic differences. Methods Th...

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Detalhes bibliográficos

Principais autores:	Yanyan Shi, Ralf Strobl, Reinhard Berner, Jakob Armann, Simone Scheithauer, Eva Grill
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2024-10-01
Colecção:	Respiratory Research
Assuntos:	SARS-CoV-2 Clinical phenotype Clustering Machine learning Prognosis
Acesso em linha:	https://doi.org/10.1186/s12931-024-03018-3
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