Cargando…
Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method
BACKGROUND: Descriptions of single clinical symptoms of coronavirus disease 2019 (COVID-19) have been widely reported. However, evidence of symptoms associations was still limited. We sought to explore the potential symptom clustering patterns and high-frequency symptom combinations of COVID-19 to e...
Autores principales: | Cheng, Xiuwei, Wan, Hongli, Yuan, Heng, Zhou, Lijun, Xiao, Chongkun, Mao, Suling, Li, Zhirui, Hu, Fengmiao, Yang, Chuan, Zhu, Wenhui, Zhou, Jiushun, Zhang, Tao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8854172/ https://www.ncbi.nlm.nih.gov/pubmed/35186839 http://dx.doi.org/10.3389/fpubh.2022.795734 |
Ejemplares similares
-
SARS-CoV-2 Seroprevalence and Profiles Among Convalescents in Sichuan Province, China
por: Zhou, Lijun, et al.
Publicado: (2021) -
Epidemiological analysis of 67 local COVID-19 clusters in Sichuan Province, China
por: Mao, Suling, et al.
Publicado: (2020) -
Clinical characteristics and clinical outcome of community clusters with SARS-CoV-2 infection
por: Zhu, Xueling, et al.
Publicado: (2023) -
Detection of SARS-CoV-2 infection clusters: The useful combination of spatiotemporal clustering and genomic analyses
por: Choi, Yangji, et al.
Publicado: (2022) -
Erratum: Detection of SARS-CoV-2 infection clusters: The useful combination of spatiotemporal clustering and genomic analyses
Publicado: (2023)