Machine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dy...
Machine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dysregulation in COVID‐19
About this item
Full title
Author / Creator
Zhou, Zhaoming , Zhou, Xiang , Cheng, Liming , Wen, Lei , An, Taixue , Gao, Heng , Deng, Hongrong , Yan, Qi , Zhang, Xinlu , Li, Youjiang , Liao, Yixing , Chen, Xin‐zu , Nie, Bin , Cheng, Jie , Deng, Guanhua , Wang, Shengqiang , Li, Juan , Yin, Hanqi , Zhang, Mengxian , Cai, Linbo , Zheng, Lei , Li, Minglun , Jones, Bleddyn , Chen, Longhua , Abdollahi, Amir , Zhou, Meijuan , Zhou, Ping‐Kun and Zhou, Cheng
Publisher
Heidelberg: John Wiley & Sons, Inc
Journal title
Language
English
Formats
Publication information
Publisher
Heidelberg: John Wiley & Sons, Inc
Subjects
More information
Scope and Contents
Contents
From a more pragmatic perspective, the early detection of patients who may experience rapid clinical deterioration will enable prompt interventions and avert disease progression.1 T cell exhaustion, immunothrombotic dysregulation, as well as complement-associated microvascular injury are considered as the hallmarks of disease severity in COVID-19.2...
Alternative Titles
Full title
Machine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dysregulation in COVID‐19
Authors, Artists and Contributors
Author / Creator
Zhou, Xiang
Cheng, Liming
Wen, Lei
An, Taixue
Gao, Heng
Deng, Hongrong
Yan, Qi
Zhang, Xinlu
Li, Youjiang
Liao, Yixing
Chen, Xin‐zu
Nie, Bin
Cheng, Jie
Deng, Guanhua
Wang, Shengqiang
Li, Juan
Yin, Hanqi
Zhang, Mengxian
Cai, Linbo
Zheng, Lei
Li, Minglun
Jones, Bleddyn
Chen, Longhua
Abdollahi, Amir
Zhou, Meijuan
Zhou, Ping‐Kun
Zhou, Cheng
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_171ff92b67e740899a74410111557efa
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_171ff92b67e740899a74410111557efa
Other Identifiers
ISSN
2001-1326
E-ISSN
2001-1326
DOI
10.1002/ctm2.523
