Editorial
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Dec 16, 2024; 12(35): 6760-6763
Published online Dec 16, 2024. doi: 10.12998/wjcc.v12.i35.6760
Intensive care unit-acquired weakness: Unveiling significant risk factors and preemptive strategies through machine learning
Xiao-Yu He, Yi-Huan Zhao, Qian-Wen Wan, Fu-Shan Tang
Xiao-Yu He, Yi-Huan Zhao, Qian-Wen Wan, Fu-Shan Tang, Department of Clinical Pharmacy, Key Laboratory of Basic Pharmacology of Guizhou Province and School of Pharmacy, Zunyi Medical University, Zunyi 563006, Guizhou Province, China
Author contributions: He XY and Zhao YH contributed equally to this work; He XY and Zhao YH contributed to the manuscript outline and composed the initial draft; He XY and Wan QW were responsible for sourcing and organizing the relevant literature; Tang FS and Zhao YH originated the concept for this manuscript; Tang FS provided supervision, reviewed the paper, and finalized the manuscript; all authors have read and approved the final manuscript.
Conflict-of-interest statement: All the authors have nothing to disclose for this article.
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/
Corresponding author: Fu-Shan Tang, PhD, Professor, Department of Clinical Pharmacy, Key Laboratory of Basic Pharmacology of Guizhou Province and School of Pharmacy, Zunyi Medical University, No. 6 Xuefu West Road, Xinpu New District, Zunyi 563006, Guizhou Province, China. fstang@vip.163.com
Received: March 18, 2024
Revised: August 22, 2024
Accepted: September 4, 2024
Published online: December 16, 2024
Processing time: 219 Days and 21.6 Hours
Core Tip

Core Tip: This editorial emphasizes the importance of recognizing the risk factors linked to intensive care unit-acquired weakness and highlights the vital role of machine learning in identifying and managing these factors to improve patient outcomes and enhance the quality of care in clinical settings.