TY - JOUR
T1 - Predicting intensive care unit-acquired weakness: A multilayer perceptron neural network approach
AU - Zuluaga Gomez, Mateo
AU - González Arroyave, Daniel
AU - Ardila, Carlos Martín
PY - 2024/4/1
Y1 - 2024/4/1
N2 - In this editorial, we comment on the article by Wang and Long, published in a recent issue of the World Journal of Clinical Cases. The article addresses the challenge of predicting intensive care unit-acquired weakness (ICUAW), a neuromuscular disorder affecting critically ill patients, by employing a novel processing strategy based on repeated machine learning. The editorial presents a dataset comprising clinical, demographic, and laboratory variables from intensive care unit (ICU) patients and employs a multilayer perceptron neural network model to predict ICUAW. The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW. This editorial contributes to the growing body of literature on predictive modeling in critical care, offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.
AB - In this editorial, we comment on the article by Wang and Long, published in a recent issue of the World Journal of Clinical Cases. The article addresses the challenge of predicting intensive care unit-acquired weakness (ICUAW), a neuromuscular disorder affecting critically ill patients, by employing a novel processing strategy based on repeated machine learning. The editorial presents a dataset comprising clinical, demographic, and laboratory variables from intensive care unit (ICU) patients and employs a multilayer perceptron neural network model to predict ICUAW. The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW. This editorial contributes to the growing body of literature on predictive modeling in critical care, offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.
KW - Computer neural network
KW - Intensive care unit-acquired weakness
KW - Intensive care unit
KW - Machine learning; Risk factors
U2 - 10.12998/wjcc.v12.i12.2023
DO - 10.12998/wjcc.v12.i12.2023
M3 - Artículo en revista científica indexada
SN - 2307-8960
VL - 12
JO - World Journal of Clinical Cases
JF - World Journal of Clinical Cases
IS - 12
ER -