The Number of Microbubbles Generated During Cardiopulmonary Bypass Can Be Estimated Using Machine Learning From Suction Flow Rate, Venous Reservoir Level, Perfusion Flow Rate, Hematocrit Level, and Blood Temperature-Reference-Cited by-同舟云学术

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The Number of Microbubbles Generated During Cardiopulmonary Bypass Can Be Estimated Using Machine Learning From Suction Flow Rate, Venous Reservoir Level, Perfusion Flow Rate, Hematocrit Level, and Blood Temperature

Published:2024 Issue: Volume:5 Page:66-74
ISSN:2644-1276
Container-title:IEEE Open Journal of Engineering in Medicine and Biology
language:
Short-container-title:IEEE Open J. Eng. Med. Biol.

Author:

Miyamoto Satoshi¹^ORCID,Soh Zu²,Okahara Shigeyuki³^ORCID,Furui Akira²^ORCID,Takasaki Taiichi⁴,Katayama Keijiro⁴,Takahashi Shinya⁴^ORCID,Tsuji Toshio²^ORCID

Affiliation:

1. Department of System Cybernetics, Graduate School of Engineering, Hiroshima University, Higashihiroshima, Japan

2. Graduate School of Advanced Science and Engineering, Hiroshima University, Higashihiroshima, Japan

3. Graduate School of Health Sciences, Junshin Gakuen University, Fukuoka, Japan

4. Department of Cardiovascular Surgery, Hiroshima University Hospital, Hiroshima, Japan

Funder

JSPS KAKENHI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8782705/10443311/10382573.pdf?arnumber=10382573

Reference43 articles.

1. Central nervous system injury associated with cardiac surgery

2. Postoperative Cognitive Dysfunction After Cardiac Surgery

3. Gas Embolism

4. Post-Arterial Filter Gaseous Microemboli Activity of Five Integral Cardiotomy Reservoirs during Venting: An In Vitro Study

5. Daughter bubble cascades produced by folding of ruptured thin films

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