Neural Network-based Estimation of Microbubbles Generated in Cardiopulmonary Bypass Circuit: A Clinical Application Study-Reference-Cited by-同舟云学术

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Neural Network-based Estimation of Microbubbles Generated in Cardiopulmonary Bypass Circuit: A Clinical Application Study

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Miyamoto Satoshi¹,Soh Zu²,Okahara Shigeyuki³,Furui Akira²,Takasaki Taiichi²,Katayama Keijiro⁴,Takahashi Shinya⁴,Tsuji Toshio⁴

Affiliation:

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

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

3. Junshin Gakuen University,Faculty of Health Sciences,Department of Medical Engineering,Fukuoka,Japan

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

Funder

JSPS

KAKENHI

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871662.pdf?arnumber=9871662

Reference14 articles.

1. The Cardiotomy Trial

2. A Novel Blood Viscosity Estimation Method Based on Pressure-Flow Characteristics of an Oxygenator During Cardiopulmonary Bypass

3. Continuous Blood Viscosity Monitoring System for Cardiopulmonary Bypass Applications

4. Neural network-based modeling of the number of microbubbles generated with four circulation factors in cardiopulmonary bypass

5. Emboli generation by the Medtronic Maxima hard shell adult venous reservoir in cardiopulmonary bypass circuits: a preliminary report

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. 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;IEEE Open Journal of Engineering in Medicine and Biology;2024

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