Cargando…
Non-contact screening system based for COVID-19 on XGBoost and logistic regression
BACKGROUND: The coronavirus disease (COVID-19) effected a global health crisis in 2019, 2020, and beyond. Currently, methods such as temperature detection, clinical manifestations, and nucleic acid testing are used to comprehensively determine whether patients are infected with the severe acute resp...
Autores principales: | Dong, Chunjiao, Qiao, Yixian, Shang, Chunheng, Liao, Xiwen, Yuan, Xiaoning, Cheng, Qin, Li, Yuxuan, Zhang, Jianan, Wang, Yunfeng, Chen, Yahong, Ge, Qinggang, Bao, Yurong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8563520/ https://www.ncbi.nlm.nih.gov/pubmed/34782110 http://dx.doi.org/10.1016/j.compbiomed.2021.105003 |
Ejemplares similares
-
Predicting ICU Mortality in Rheumatic Heart Disease: Comparison of XGBoost and Logistic Regression
por: Xu, Yixian, et al.
Publicado: (2022) -
XGBoost algorithm and logistic regression to predict the postoperative 5-year outcome in patients with glioma
por: Yan, Zhiqiang, et al.
Publicado: (2022) -
Prediction Model of Bone Marrow Infiltration in Patients with Malignant Lymphoma Based on Logistic Regression and XGBoost Algorithm
por: Huang, Yongfen, et al.
Publicado: (2022) -
Prediction Model of Postoperative Severe Hypocalcemia in Patients with Secondary Hyperparathyroidism Based on Logistic Regression and XGBoost Algorithm
por: Ding, Chao, et al.
Publicado: (2022) -
Assessing the Nationwide COVID-19 Risk in Mexico through the Lens of Comorbidity by an XGBoost-Based Logistic Regression Model
por: Venancio-Guzmán, Sonia, et al.
Publicado: (2022)