Cargando…
A complete blood count-based multivariate model for predicting the recovery of patients with moderate COVID-19: a retrospective study
Many resource-limited countries need an efficient and convenient method to assess disease progression in patients with coronavirus disease 2019 (COVID-19). This study developed and validated a complete blood count-based multivariate model for predicting the recovery of patients with moderate COVID-1...
Autores principales: | Wang, Yiting, Li, Xuewen, Xu, Jiancheng, Zhou, Qi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617603/ https://www.ncbi.nlm.nih.gov/pubmed/36309538 http://dx.doi.org/10.1038/s41598-022-23285-8 |
Ejemplares similares
-
Early changes in laboratory tests predict liver function damage in patients with moderate coronavirus disease 2019: a retrospective multicenter study
por: Wang, Yiting, et al.
Publicado: (2022) -
Development and comparison of machine learning-based models for predicting heart failure after acute myocardial infarction
por: Li, Xuewen, et al.
Publicado: (2023) -
Potential Predictive Value of miR-125b-5p, miR-155-5p and Their Target Genes in the Course of COVID-19
por: Li, Xuewen, et al.
Publicado: (2022) -
Predictions of CD4 lymphocytes’ count in HIV patients from complete blood count
por: Rodríguez, Javier O, et al.
Publicado: (2013) -
A Multivariate Poisson Deep Learning Model for Genomic Prediction of Count Data
por: Montesinos-López, Osval Antonio, et al.
Publicado: (2020)