Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction

Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction

Abstract The advancement of the Internet of Medical Things (IoMT) has revolutionized data acquisition and processing in critical care settings. Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computin...

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Bibliographic Details
Main Authors: Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Internet of medical things
Edge-computing
Machine learning
Extubation
Clinical decision support system
Online Access:https://doi.org/10.1038/s41598-025-02317-z
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https://doi.org/10.1038/s41598-025-02317-z

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