Early-stage predictors of deterioration among 3145 nonsevere SARS-CoV-2-infected people community-isolated in Wuhan, China: A combination of machine learning algorithms and competing risk survival analyses.
Kaiyuan MinZhenshun ChengJiangfeng LiuYanhong FangWeichen WangYehong YangPascal GeldsetzerTill BärnighausenJuntao YangDepei LiuSimiao ChenChen WangPublished in: Journal of evidence-based medicine (2023)
Early-stage prediction of COVID-19 deterioration can be made with inexpensive-to-measure variables, such as demographic characteristics, severity upon admission, observable symptoms, and self-reported comorbid diseases, among asymptomatic people and mildly to moderately symptomatic patients.
Keyphrases
- early stage
- sars cov
- machine learning
- coronavirus disease
- end stage renal disease
- chronic kidney disease
- emergency department
- healthcare
- newly diagnosed
- peritoneal dialysis
- artificial intelligence
- respiratory syndrome coronavirus
- prognostic factors
- deep learning
- sleep quality
- squamous cell carcinoma
- sentinel lymph node
- big data
- rectal cancer