Computer-Aided Diagnosis System of Fetal Hypoxia Incorporating Recurrence Plot With Convolutional Neural Network

dc.contributor.author	Zhao, Zhidong
dc.contributor.author	Zhang, Yang
dc.contributor.author	Comert, Zafer
dc.contributor.author	Deng, Yanjun
dc.date.accessioned	2021-12-16T09:07:00Z
dc.date.available	2021-12-16T09:07:00Z
dc.date.issued	2019
dc.identifier.issn	1664-042X
dc.identifier.uri	https://doi.org/10.3389/fphys.2019.00255
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10125
dc.description.abstract	Background: Electronic fetal monitoring (EFM) is widely applied as a routine diagnostic tool by clinicians using fetal heart rate (FHR) signals to prevent fetal hypoxia. However, visual interpretation of the FHR usually leads to significant inter-observer
dc.description.sponsorship	Welfare Project of the Science Technology Department of Zhejiang Province [2017C31046, 2016C33079]; Smart City Collaborative Innovation Center of Zhejiang Province; Graduate Research Innovation Project of Hangzhou Dianzi University [CXJJ2017038]
dc.language.iso	English
dc.publisher	Frontıers Medıa Sa
dc.rights	Green Published, gold
dc.source	Frontıers In Physıology
dc.title	Computer-Aided Diagnosis System of Fetal Hypoxia Incorporating Recurrence Plot With Convolutional Neural Network
dc.type	Article
dc.identifier.doi	10.3389/fphys.2019.00255
dc.identifier.wos	WOS:000460868100001
dc.identifier.volume	10

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