Algorithms 2009, 2(1), 19-30; doi:10.3390/a2010019

Neural Network Analysis and Evaluation of the Fetal Heart Rate

1email, 1, 2,* email and 3email
Received: 21 November 2008; in revised form: 4 January 2009 / Accepted: 8 January 2009 / Published: 16 January 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The aim of the present study is to obtain a highly objective automatic fetal heart rate (FHR) diagnosis. The neural network software was composed of three layers with the back propagation, to which 8 FHR data, including sinusoidal FHR, were input and the system was educated by the data of 20 cases with a known outcome. The output was the probability of a normal, intermediate, or pathologic outcome. The neural index studied prolonged monitoring. The neonatal states and the FHR score strongly correlated with the outcome probability. The neural index diagnosis was correct. The completed software was transferred to other computers, where the system function was correct.
Keywords: Neural network; fetus; neonate; fetal heart rate (FHR); sinusoidal FHR; non-reassuring fetal status; neonatal asphyxia
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MDPI and ACS Style

Noguchi, Y.; Matsumoto, F.; Maeda, K.; Nagasawa, T. Neural Network Analysis and Evaluation of the Fetal Heart Rate. Algorithms 2009, 2, 19-30.

AMA Style

Noguchi Y, Matsumoto F, Maeda K, Nagasawa T. Neural Network Analysis and Evaluation of the Fetal Heart Rate. Algorithms. 2009; 2(1):19-30.

Chicago/Turabian Style

Noguchi, Yasuaki; Matsumoto, Fujihiko; Maeda, Kazuo; Nagasawa, Takashi. 2009. "Neural Network Analysis and Evaluation of the Fetal Heart Rate." Algorithms 2, no. 1: 19-30.

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