A Comparative Study of Deep Learning Models for Patient-Ventilator Asynchrony Classification using Phase Space Reconstruction-Reference-Cited by-同舟云学术

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A Comparative Study of Deep Learning Models for Patient-Ventilator Asynchrony Classification using Phase Space Reconstruction

Published:2023-10-19 Issue: Volume:12 Page:1-5
ISSN:
Container-title:2023 IEEE Biomedical Circuits and Systems Conference (BioCAS)
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Author:

Ma Liang¹,Xiong Fuhai¹,Huang Zhiwen²,Omisore Olatunji¹,Wang Lei¹,Yan Yan¹

Affiliation:

1. Chinese Academy of Sciences,Shenzhen Institute of Advanced Technology,Shenzhen,China

2. Shenzhen Mindray Bio-Medical Electronics Co., Ltd,Shenzhen,China

Funder

National Key Research and Development Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10388488/10388438/10388786.pdf?arnumber=10388786

Reference23 articles.

1. Asynchronies during mechanical ventilation are associated with mortality

2. Risk Factors for Patient–Ventilator Asynchrony and Its Impact on Clinical Outcomes: Analytics Based on Deep Learning Algorithm

3. Patient–ventilator asynchrony, impact on clinical outcomes and effectiveness of interventions: a systematic review and meta-analysis

4. A machine learning method for automatic detection and classification of patient-ventilator asynchrony

5. Identifying and managing patient–ventilator asynchrony: An international survey

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