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Articles in Press
3/27/2024 5:28:52 AM | Browse: 36 | Download: 0
Category |
Multidisciplinary Sciences |
Manuscript Type |
Editorial |
Article Title |
Pioneering role of machine learning in unveiling intensive care unit-acquired weakness
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Manuscript Source |
Invited Manuscript |
All Author List |
Silvano Dragonieri |
Funding Agency and Grant Number |
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Corresponding Author |
Silvano Dragonieri, MD, PhD, Associate Professor, Department of Respiratory Diseases, University of Bari, Piazza Giulio Cesare 11, Bari 70124, Italy. silvano.dragonieri@uniba.it |
Key Words |
Intensive care unit-acquired weakness; Machine learning; Multilayer perceptron neural network; Predictive medicine; Interdisciplinary collaboration |
Core Tip |
This editorial leverages machine learning, specifically a multilayer perceptron neural network, to pinpoint key risk factors for intensive care unit-acquired weakness (ICU-AW), emphasizing the critical roles of ICU stay duration and mechanical ventilation. It heralds a paradigm shift towards data-driven, predictive medicine in critical care, advocating for the integration of artificial intelligence in clinical practices and interdisciplinary collaboration to enhance patient care outcomes. |
Citation |
Dragonieri S. Pioneering role of machine learning in unveiling intensive care unit-acquired weakness. World J Clin Cases 2024; 12(13): 2157-2159 |
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Received |
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2024-02-21 11:17 |
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Peer-Review Started |
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2024-02-23 03:12 |
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To Make the First Decision |
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Return for Revision |
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2024-03-06 21:17 |
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Revised |
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2024-03-07 15:04 |
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Second Decision |
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2024-03-27 02:36 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2024-03-27 05:28 |
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Articles in Press |
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2024-03-27 05:28 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2024-04-17 06:16 |
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) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
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