A machine learning-based phenotype for long COVID in children: An EHR-based study from the RECOVER program

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As clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data. In this study, w...

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Detalles Bibliográficos
Autores principales: Lorman, Vitaly, Razzaghi, Hanieh, Song, Xing, Morse, Keith, Utidjian, Levon, Allen, Andrea J., Rao, Suchitra, Rogerson, Colin, Bennett, Tellen D., Morizono, Hiroki, Eckrich, Daniel, Jhaveri, Ravi, Huang, Yungui, Ranade, Daksha, Pajor, Nathan, Lee, Grace M., Forrest, Christopher B., Bailey, L. Charles
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414557/
https://www.ncbi.nlm.nih.gov/pubmed/37561683
http://dx.doi.org/10.1371/journal.pone.0289774

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414557/
https://www.ncbi.nlm.nih.gov/pubmed/37561683
http://dx.doi.org/10.1371/journal.pone.0289774

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