Publication Name	World Journal of Clinical Cases
Manuscript ID	93182
Country	Italy

Category	Multidisciplinary Sciences
Manuscript Type	Editorial
Article Title	Pioneering role of machine learning in unveiling intensive care unit-acquired weakness
Manuscript Source	Invited Manuscript
All Author List	Silvano Dragonieri
Funding Agency and Grant Number
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

Received	2024-02-21 11:17
Peer-Review Started	2024-02-23 03:12
To Make the First Decision
Return for Revision	2024-03-06 21:17
Revised	2024-03-07 15:04
Second Decision	2024-03-27 02:36
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2024-03-27 05:28
Articles in Press	2024-03-27 05:28
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-04-17 06:16

ISSN	2307-8960 (online)
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