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dc.contributor.author Yang, Hyun-Lim ko
dc.contributor.author Lee, Hyung-Chul ko
dc.contributor.author Jung, Chul-Woo ko
dc.contributor.author Kim, Min-Soo ko
dc.date.accessioned 2021-01-29T07:32:28Z -
dc.date.available 2021-01-29T07:32:28Z -
dc.date.created 2021-01-28 -
dc.date.issued 2020-10-27 -
dc.identifier.citation 20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020, pp.662 - 666 -
dc.identifier.isbn 9781728195742 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12915 -
dc.description.abstract Cardiac output monitoring plays an important role in intraoperative or intensive care medicine. Arterial pressure waveform derived cardiac output monitoring has been mainly used for real clinical fields despite its inexact output because gold standard thermodilution based cardiac output monitoring is too invasive to use it widely. In this study, we propose DLAPCO, the novel deep learning method for the more accurate and age-agnostic arterial pressure waveform derived cardiac output monitoring. DLAPCO exploits two attention mechanism to calibrate the model's output to medical procedure or overcome the locality of convolutional neural network in analyzing raw vital signs. Through the experiments using the real-world hospital intraoperative data, we have shown that DLAPCO significantly outperforms the commercial arterial pressure waveform derived cardiac output monitoring device which use demographic information. © 2020 IEEE. -
dc.language English -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.title A Deep Learning Method for Intraoperative Age-agnostic and Disease-specific Cardiac Output Monitoring from Arterial Blood Pressure -
dc.type Conference -
dc.identifier.doi 10.1109/BIBE50027.2020.00112 -
dc.identifier.scopusid 2-s2.0-85099603409 -
dc.type.local Article(Overseas) -
dc.type.rims CONF -
dc.description.journalClass 1 -
dc.contributor.localauthor Kim, Min-Soo -
dc.contributor.nonIdAuthor Lee, Hyung-Chul -
dc.contributor.nonIdAuthor Jung, Chul-Woo -
dc.identifier.citationStartPage 662 -
dc.identifier.citationEndPage 666 -
dc.identifier.citationTitle 20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020 -
dc.identifier.conferencecountry US -
dc.identifier.conferencelocation Virtual Conference -


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