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Neural Network Analysis and Evaluation of the Fetal Heart Rate

1
Department of Applied Physics, National Defense Academy, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan
2
Professor Emeritus, Department of Obstetrics and Gynecology, Tottori University. Home: 3-125, Nadamachi, Yonago, Tottori, 683-0835, Japan
3
Department of Information Technology, TOITU Ltd., 1-5-10, Ebisu-west, Shibuyaku, Tokyo, 150-0021, Japan
*
Author to whom correspondence should be addressed.
Algorithms 2009, 2(1), 19-30; https://doi.org/10.3390/a2010019
Received: 21 November 2008 / Revised: 4 January 2009 / Accepted: 8 January 2009 / Published: 16 January 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
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. View Full-Text
Keywords: Neural network; fetus; neonate; fetal heart rate (FHR); sinusoidal FHR; non-reassuring fetal status; neonatal asphyxia Neural network; fetus; neonate; fetal heart rate (FHR); sinusoidal FHR; non-reassuring fetal status; neonatal asphyxia
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Noguchi, Y.; Matsumoto, F.; Maeda, K.; Nagasawa, T. Neural Network Analysis and Evaluation of the Fetal Heart Rate. Algorithms 2009, 2, 19-30.

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