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10/15/2021 9:45:09 AM | Browse: 358 | Download: 829
Publication Name World Journal of Clinical Cases
Manuscript ID 68853
Country China
Received
2021-06-06 11:49
Peer-Review Started
2021-06-06 11:49
To Make the First Decision
Return for Revision
2021-06-25 09:28
Revised
2021-07-07 04:10
Second Decision
2021-07-22 03:02
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2021-07-22 05:20
Articles in Press
2021-07-22 05:20
Publication Fee Transferred
Edit the Manuscript by Language Editor
2021-07-31 18:43
Typeset the Manuscript
2021-10-11 06:12
Publish the Manuscript Online
2021-10-15 09:45
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: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright © The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Anesthesiology
Manuscript Type Retrospective Study
Article Title Development of a random forest model for hypotension prediction after anesthesia induction for cardiac surgery
Manuscript Source Unsolicited Manuscript
All Author List Xuan-Fa Li, Yong-Zhen Huang, Jing-Ying Tang, Rui-Chen Li and Xiao-Qi Wang
ORCID
Author(s) ORCID Number
Xuan-Fa Li http://orcid.org/0000-0003-3614-8691
Yong-Zhen Huang http://orcid.org/0000-0001-9394-2221
Jing-Ying Tang http://orcid.org/0000-0001-8007-6192
Rui-Chen Li http://orcid.org/0000-0002-5696-316X
Xiao-Qi Wang http://orcid.org/0000-0002-4587-0056
Funding Agency and Grant Number
Corresponding Author Xiao-Qi Wang, MD, PhD, Associate Professor, Department of Anesthesiology, The Second Affiliated Hospital of Hainan Medical University, No. 368 Yehai Avenue, Longhua District, Haikou 570311, Hainan Province, China. wxq201904@163.com
Key Words Anesthesia; Hypotension prediction; Cardiac surgery; Random forest; Machine learning
Core Tip This was a retrospective study intended to develop a prediction model for hypotensive events after anesthesia during cardiac surgery. A machine-learning technique-random forest-was applied to establish a predictive algorithm using preoperative data. The “features ranked by importance” was also developed in this study. This new type of prediction model can be potentially applied to foresee hypotension events toward avoiding the occurrence of any potential adverse events.
Publish Date 2021-10-15 09:45
Citation Li XF, Huang YZ, Tang JY, Li RC, Wang XQ. Development of a random forest model for hypotension prediction after anesthesia induction for cardiac surgery. World J Clin Cases 2021; 9(29): 8729-8739
URL https://www.wjgnet.com/2307-8960/full/v9/i29/8729.htm
DOI https://dx.doi.org/10.12998/wjcc.v9.i29.8729
Full Article (PDF) WJCC-9-8729.pdf
Full Article (Word) WJCC-9-8729.docx
Manuscript File 68853-Review-FilipodiaCL.docx
Answering Reviewers 68853-Answering reviewers.pdf
Audio Core Tip 68853-Audio core tip.m4a
Biostatistics Review Certificate 68853-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form 68853-Conflict-of-interest statement.pdf
Copyright License Agreement 68853-Copyright license agreement.pdf
Signed Informed Consent Form(s) or Document(s) 68853-Informed consent statement.pdf
Institutional Review Board Approval Form or Document 68853-Institutional review board statement.pdf
Non-Native Speakers of English Editing Certificate 68853-Language certificate.pdf
Peer-review Report 68853-Peer-review(s).pdf
Scientific Misconduct Check 68853-Bing-Gong ZM-1.png
Scientific Misconduct Check 68853-CrossCheck.png
Scientific Misconduct Check 68853-Bing-Gong ZM-2.png
Scientific Misconduct Check 68853-Scientific misconduct check.pdf
Scientific Editor Work List 68853-Scientific editor work list.pdf