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

Mostrar otras versiones (1)

BACKGROUND: 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. METH...

Descripción completa

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: Cold Spring Harbor Laboratory 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810222/
https://www.ncbi.nlm.nih.gov/pubmed/36597534
http://dx.doi.org/10.1101/2022.12.22.22283791
Mostrar todas las versiones(2)

Ejemplares similares