Effects of Data Structure in Convolutional Neural Network for Detection of Asynchronous Breathing in Mechanical Ventilation Treatment-Reference-Cited by-同舟云学术

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Effects of Data Structure in Convolutional Neural Network for Detection of Asynchronous Breathing in Mechanical Ventilation Treatment

Published:2022-12-07 Issue: Volume: Page:
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Container-title:2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)
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Author:

Ang Christopher Yew Shuen¹,Loo Nien Loong²,Chiew Yeong Shiong¹,Tan Chee Pin¹,Nor Mohd Basri Mat³,Chase J. Geoffrey⁴

Affiliation:

1. Monash University Malaysia,School of Engineering,Subang Jaya,Malaysia,47500

2. Selangor Human Resource Development Centre,Shah Alam,Malaysia,40100

3. International Islamic University Malaysia,Kulliyah of Medicine,Kuantan,Malaysia,25200

4. University of Canterbury,Centre of Bioengineering,Christchurch,New Zealand,8041

Funder

Ministry of Higher Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10079231/10079241/10079652.pdf?arnumber=10079652

Reference20 articles.

1. Clinical Utilisation of Respiratory Elastance (CURE): Pilot Trials for the Optimisation of Mechanical Ventilation Settings for the Critically Ill;davidson;IFAC Proceedings Volumes,2014

2. Classification Patient-Ventilator Asynchrony with Dual-Input Convolutional Neural Network

3. Patient-ventilator asynchrony during assisted mechanical ventilation

4. Clinical Application of Respiratory Elastance (CARE Trial) for Mechanically Ventilated Respiratory Failure Patients: A Model-based Study

5. Assessing mechanical ventilation asynchrony through iterative airway pressure reconstruction

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploring variable observational time windows for patient–ventilator asynchrony during mechanical ventilation treatment;IFAC Journal of Systems and Control;2024-09

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