Deep learning integration of chest computed tomography and plasma proteomics to identify novel aspects of severe COVID-19 pneumonia

Deep learning integration of chest computed tomography and plasma proteomics to identify novel aspects of severe COVID-19 pneumonia

Background: Heterogeneity is a critical characteristic of severe coronavirus disease 2019 (COVID-19) pneumonia. Integrating chest computed tomography (CT) imaging and plasma proteomics holds the potential to elucidate Image-Expression Axes (IEAs) that can effectively address this disease heterogenei...

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Bibliographic Details
Main Authors: Yucai Hong, Lin Chen, Yang Yu, Ziyue Zhao, Ronghua Wu, Rui Gong, Yandong Cheng, Lingmin Yuan, Shaojun Zheng, Cheng Zheng, Ronghai Lin, Jianping Chen, Kangwei Sun, Ping Xu, Li Ye, Chaoting Han, Xihao Zhou, Yaqing Liu, Jianhua Yu, Yaqin Zheng, Jie Yang, Jiajie Huang, Juan Chen, Junjie Fang, Chensong Chen, Bo Fan, Honglong Fang, Baning Ye, Xiyun Chen, Xiaoli Qian, Junxiang Chen, Haitao Yu, Jun Zhang, Xi-Ming Pan, Yi-Xing Zhan, You-Hai Zheng, Zhang-Hong Huang, Chao Zhong, Ning Liu, Hongying Ni, Gengsheng Zhang, Zhongheng Zhang
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Journal of Intensive Medicine
Subjects:
Covid-19
Systemic inflammatory response syndrome
Heterogeneity
Self-supervised representation learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2667100X2400121X
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