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3/17/2023 7:11:35 AM | Browse: 23 | Download: 0
Publication Name World Journal of Clinical Cases
Manuscript ID 81109
Country/Territory China
Category Respiratory System
Manuscript Type Observational Study
Article Title Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores
Manuscript Source Unsolicited Manuscript
All Author List Qiu-Yu Li, Zi-Han Pan, Zhuo-Yu An, Zi-Zhen Wang, Yi-Ren Wang, Xi-Gong Zhang and Ning Shen
Funding Agency and Grant Number
Funding Agency Grant Number
National Natural Science Foundation of China 81900641
the Research Funding of Peking University BMU2021MX020 and BMU2022MX008
Corresponding Author Ning Shen, Department of Respiratory and Critical Care Medicine, Peking University Third Hospital, No. 49 Huayuan North Road, Haidian District, Beijing 100191, China. shenning1972@126.com
Key Words COVID-19; Clinical prediction model; Electron computed tomography; Machine learning
Core Tip The computed tomography (CT) score is a relatively objective and clinically accessible semiquantitative assessment tool for patients with coronavirus disease 2019 (COVID-19). The CT scores of common, severe, and critically ill patients showed different trends, and there were differences between the groups of patients as the disease progressed. Patients who are recovering from the disease can be monitored via CT at reduced intervals to reduce their radiation exposure and financial burden. The 2 wk CT scores of the patients were important for predicting disease deterioration in hospitalized patients who have an average admission severity rating. The qSOFA score, aspartate aminotransferase, oxygenation, and dyspnea were important for the prediction of severe/critical COVID-19 disease.
Citation Li QY, An ZY, Pan ZH, Wang ZZ, Wang YR, Zhang XG, Shen N. Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores. World J Clin Cases 2023; In press
2022-11-05 01:00
Peer-Review Started
2022-11-01 13:30
To Make the First Decision
Return for Revision
2023-01-30 02:27
2023-02-12 17:49
Second Decision
2023-03-17 02:37
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2023-03-17 07:11
Articles in Press
2023-03-17 07:11
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 2307-8960 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright © The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
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Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Assistant Editor Assistant Editor
Science Editor Yan-Xia Xing
Reviewer Code 05722553, and 06025907
Editorial Director
Journal Chief Editor
Company Chief Editor Jin-Lei Wang
Language Editor
Production Editor
Responsible Production Editor
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Proofing Editorial Director Jin-Lei Wang
Proofing Editor-in-Chief Lian-Sheng Ma