Open AccessMachine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dysregulation in COVID‐19
Author(s) -
Zhou Zhaoming,
Zhou Xiang,
Cheng Liming,
Wen Lei,
An Taixue,
Gao Heng,
Deng Hongrong,
Yan Qi,
Zhang Xinlu,
Li Youjiang,
Liao Yixing,
Chen Xinzu,
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 PingKun,
Zhou Cheng
Publication year - 2021
Publication title -
clinical and translational medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.125
H-Index - 1
ISSN - 2001-1326
DOI - 10.1002/ctm2.523
Subject(s) - covid-19 , computer science , medicine , machine learning , artificial intelligence , algorithm , virology , disease , outbreak , infectious disease (medical specialty)