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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

Crossref DOI link: https://doi.org/10.1186/s12931-024-03018-3

Published Online: 2024-10-30

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Shi, Yanyan

Strobl, Ralf

Berner, Reinhard

Armann, Jakob

Scheithauer, Simone

Grill, Eva
Funding

Funding for this research was provided by:

Ludwig-Maximilians-Universität München
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Text and Data Mining valid from 2024-10-30

Version of Record valid from 2024-10-30
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Article History

Received: 17 July 2024

Accepted: 20 October 2024

First Online: 30 October 2024

Declarations

:

: The funders of this study had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

: The DGPI registry was approved by the Ethics Committee of the Technische Universität (TU) Dresden (BO-EK-110032020).

: Not Applicable.

: None.

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