Early prediction model for disease progression of COVID-19 patients based on XGBoost: establishment and evaluation
Journal of Army Medical University
; 44(3):195-202, 2022.
Article
in Chinese
| CAB Abstracts | ID: covidwho-1841727
ABSTRACT
Objective:
To construct an XGBoost prediction model to predict disease severity of COVID-19 based on clinical characteristics dataset of COVID-19 patients.
Mathematics and Statistics [ZZ100]; Prion, Viral, Bacterial and Fungal Pathogens of Humans [VV210]; prediction; mathematical models; coronavirus disease 2019; human diseases; viral diseases; disease course; Severe acute respiratory syndrome coronavirus 2; man; China; Severe acute respiratory syndrome-related coronavirus; Betacoronavirus; Coronavirinae; Coronaviridae; Nidovirales; positive-sense ssRNA Viruses; ssRNA Viruses; RNA Viruses; viruses; Homo; Hominidae; primates; mammals; vertebrates; Chordata; animals; eukaryotes; APEC countries; East Asia; Asia; high Human Development Index countries; upper-middle income countries; SARS-CoV-2; People's Republic of China; viral infections; disease progression
Full text:
Available
Collection:
Databases of international organizations
Database:
CAB Abstracts
Type of study:
Experimental Studies
/
Prognostic study
Language:
Chinese
Journal:
Journal of Army Medical University
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS