Editorial
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Jun 26, 2024; 12(18): 3288-3290
Published online Jun 26, 2024. doi: 10.12998/wjcc.v12.i18.3288
Unveiling significant risk factors for intensive care unit-acquired weakness: Advancing preventive care
Chun-Yao Cheng, Wen-Rui Hao, Tzu-Hurng Cheng
Chun-Yao Cheng, Department of Medical Education, National Taiwan University Hospital, Taipei 100225, Taiwan
Wen-Rui Hao, Division of Cardiology, Department of Internal Medicine, Shuang Ho Hospital, Ministry of Health and Welfare, Taipei Medical University, New Taipei 23561, Taiwan
Wen-Rui Hao, Division of Cardiology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11002, Taiwan
Tzu-Hurng Cheng, Department of Biochemistry, School of Medicine, College of Medicine, China Medical University, Taichung 404333, Taiwan
Co-first authors: Chun-Yao Cheng and Wen-Rui Hao.
Author contributions: Cheng CY wrote the paper; Hao WR and Cheng TH revised the paper. All authors have read and approved the final manuscript. Cheng CY and Hao WR contributed equally to this work as co-first authors.
Supported by China Medical University, No. CMU111-MF-102.
Conflict-of-interest statement: The authors declare having no conflicts of interest.
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: Tzu-Hurng Cheng, PhD, Professor, Department of Biochemistry, School of Medicine, College of Medicine, China Medical University, No. 91 Xueshi Road, North District, Taichung 404333, Taiwan. thcheng@mail.cmu.edu.tw
Received: February 24, 2024
Revised: April 23, 2024
Accepted: April 25, 2024
Published online: June 26, 2024
Processing time: 114 Days and 22.3 Hours
Core Tip

Core Tip: This editorial comment on the published article related to the potential of artificial intelligence (AI) and machine learning in predicting and mitigating intensive care unit-acquired weakness (ICU-AW) in critically ill patients. By identifying key risk factors and developing a predictive model, clinicians can optimize patient care and improve outcomes. Early prediction and intervention based on AI-driven insights may lead to more personalized and effective strategies for preventing ICU-AW.