Prediction of COVID-19 Severity Using Chest Computed Tomography and Laboratory Measurements: Evaluation Using a Machine Learning Approach
BackgroundMost of the mortality resulting from COVID-19 has been associated with severe disease. Effective treatment of severe cases remains a challenge due to the lack of early detection of the infection. ObjectiveThis study aimed to develop an effective predicti...
Main Authors: | Li, Daowei, Zhang, Qiang, Tan, Yue, Feng, Xinghuo, Yue, Yuanyi, Bai, Yuhan, Li, Jimeng, Li, Jiahang, Xu, Youjun, Chen, Shiyu, Xiao, Si-Yu, Sun, Muyan, Li, Xiaona, Zhu, Fang |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2020-11-01
|
Series: | JMIR Medical Informatics |
Online Access: | http://medinform.jmir.org/2020/11/e21604/ |
Similar Items
-
Automatically Generate a Simplified Chest Atlas from the Chest Computed Tomography Using Morphology, Image Segmentation and K-means
by: Yue-Yang Tsai, et al.
Published: (2009) -
What is the potential for over-compression using current paediatric chest compression guidelines? — A chest computed tomography study
by: Gene Yong-Kwang Ong, et al.
Published: (2021-06-01) -
Findings in Chest High-Resolution Computed Tomography in Severe Asthma
by: Borja Segade, J., et al.
Published: (2022) -
Accuracy of chest radiography versus chest computed tomography in hemodynamically stable patients with blunt chest trauma
by: Chardoli Mojtaba, et al.
Published: (2013-12-01) -
Measuring pulmonary function in COPD using quantitative chest computed tomography analysis
by: Jens T. Bakker, et al.
Published: (2021-07-01)