Computer-aided diagnosis system of fetal hypoxia incorporating recurrence plot with convolutional neural network

dc.contributor.author	Zhao, Z.
dc.contributor.author	Zhang, Y.
dc.contributor.author	Comert, Z.
dc.contributor.author	Deng, Y.
dc.date.accessioned	2021-12-16T10:12:03Z
dc.date.available	2021-12-16T10:12:03Z
dc.date.issued	2019
dc.identifier.issn	1664042X
dc.identifier.uri	https://doi.org/10.3389/fphys.2019.00255
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/12954
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	Hangzhou Dianzi University, HDU; Science and Technology Department of Zhejiang Province: 2016C33079, 2017C31046
dc.language.iso	English
dc.publisher	Frontiers Media S.A.
dc.rights	All Open Access, Gold, Green
dc.source	Frontiers in Physiology
dc.title	Computer-aided diagnosis system of fetal hypoxia incorporating recurrence plot with convolutional neural network
dc.type	Article
dc.identifier.issue	MAR
dc.identifier.doi	10.3389/fphys.2019.00255
dc.identifier.scopus	2-s2.0-85066440932
dc.identifier.volume	10

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