Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach

Kuei Hung Shen; Yun Ju Yu; Szu Yin Chen; En Ming Chang; Hsiu Li Wu; Cheng Kuan Lin; Yu Chee Tseng

doi:10.1109/APWCS60142.2023.10234048

Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach

Kuei Hung Shen^*, Yun Ju Yu, Szu Yin Chen, En Ming Chang, Hsiu Li Wu, Cheng Kuan Lin, Yu Chee Tseng

^*此作品的通信作者

研究成果: Conference contribution › 同行評審

摘要

Mechanical Ventilation (MV) is a type of therapy that helps patients breathe or breathes for patients when they can't breathe on their own. Doctors and therapists determine whether a patient is ready for weaning of mechanical ventilation based on vitals and various medical test results. This study explores deep learning methods applied to prediction of mechanical ventilator weaning outcome using multiple physiological parameters. Our experiments showed a validation accuracy of 0.682 with limited samples and less features compared to similar studies. We expect to see improved performance with more data and features collected.

原文	English
主出版物標題	Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023
發行者	Institute of Electrical and Electronics Engineers Inc.
ISBN（電子）	9798350316803
DOIs	https://doi.org/10.1109/APWCS60142.2023.10234048
出版狀態	Published - 2023
事件	2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023 - Tainan City, 台灣持續時間: 23 8月 2023 → 25 8月 2023

出版系列

名字	Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023

Conference

Conference	2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023
國家/地區	台灣
城市	Tainan City
期間	23/08/23 → 25/08/23

存取文件

10.1109/APWCS60142.2023.10234048

其它文件與鏈接

Link to publication in Scopus

引用此

Shen, K. H., Yu, Y. J., Chen, S. Y., Chang, E. M., Wu, H. L., Lin, C. K., & Tseng, Y. C. (2023). Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach. 於 Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023 (Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APWCS60142.2023.10234048

@inproceedings{4b338d07f78f48cc9f804512092f0272,

title = "Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach",

abstract = "Mechanical Ventilation (MV) is a type of therapy that helps patients breathe or breathes for patients when they can't breathe on their own. Doctors and therapists determine whether a patient is ready for weaning of mechanical ventilation based on vitals and various medical test results. This study explores deep learning methods applied to prediction of mechanical ventilator weaning outcome using multiple physiological parameters. Our experiments showed a validation accuracy of 0.682 with limited samples and less features compared to similar studies. We expect to see improved performance with more data and features collected.",

keywords = "Artificial Intelligence, Deep Learning, Weaning from Mechanical Ventilator",

author = "Shen, {Kuei Hung} and Yu, {Yun Ju} and Chen, {Szu Yin} and Chang, {En Ming} and Wu, {Hsiu Li} and Lin, {Cheng Kuan} and Tseng, {Yu Chee}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023 ; Conference date: 23-08-2023 Through 25-08-2023",

year = "2023",

doi = "10.1109/APWCS60142.2023.10234048",

language = "English",

series = "Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023",

address = "美國",

}

Shen, KH, Yu, YJ, Chen, SY, Chang, EM, Wu, HL, Lin, CK & Tseng, YC 2023, Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach. 於 Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023. Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023, Institute of Electrical and Electronics Engineers Inc., 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023, Tainan City, 台灣, 23/08/23. https://doi.org/10.1109/APWCS60142.2023.10234048

Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach. / Shen, Kuei Hung; Yu, Yun Ju; Chen, Szu Yin 等.
Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023).

研究成果: Conference contribution › 同行評審

TY - GEN

T1 - Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach

AU - Shen, Kuei Hung

AU - Yu, Yun Ju

AU - Chen, Szu Yin

AU - Chang, En Ming

AU - Wu, Hsiu Li

AU - Lin, Cheng Kuan

AU - Tseng, Yu Chee

PY - 2023

Y1 - 2023

N2 - Mechanical Ventilation (MV) is a type of therapy that helps patients breathe or breathes for patients when they can't breathe on their own. Doctors and therapists determine whether a patient is ready for weaning of mechanical ventilation based on vitals and various medical test results. This study explores deep learning methods applied to prediction of mechanical ventilator weaning outcome using multiple physiological parameters. Our experiments showed a validation accuracy of 0.682 with limited samples and less features compared to similar studies. We expect to see improved performance with more data and features collected.

AB - Mechanical Ventilation (MV) is a type of therapy that helps patients breathe or breathes for patients when they can't breathe on their own. Doctors and therapists determine whether a patient is ready for weaning of mechanical ventilation based on vitals and various medical test results. This study explores deep learning methods applied to prediction of mechanical ventilator weaning outcome using multiple physiological parameters. Our experiments showed a validation accuracy of 0.682 with limited samples and less features compared to similar studies. We expect to see improved performance with more data and features collected.

KW - Artificial Intelligence

KW - Deep Learning

KW - Weaning from Mechanical Ventilator

UR - http://www.scopus.com/inward/record.url?scp=85173021828&partnerID=8YFLogxK

U2 - 10.1109/APWCS60142.2023.10234048

DO - 10.1109/APWCS60142.2023.10234048

M3 - Conference contribution

AN - SCOPUS:85173021828

T3 - Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023

BT - Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023

Y2 - 23 August 2023 through 25 August 2023

ER -

Shen KH, Yu YJ, Chen SY, Chang EM, Wu HL, Lin CK 等. Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach. 於 Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings - 2023 VTS Asia Pacific Wireless Communications Symposium, APWCS 2023). doi: 10.1109/APWCS60142.2023.10234048

Prediction of Mechanical Ventilator Weaning Outcome - A Deep Learning Approach

摘要

出版系列

Conference

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指紋

引用此