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Neural Network Analysis and Evaluation of the Fetal Heart Rate
Department of Applied Physics, National Defense Academy, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan
Professor Emeritus, Department of Obstetrics and Gynecology, Tottori University. Home: 3-125, Nadamachi, Yonago, Tottori, 683-0835, Japan
Department of Information Technology, TOITU Ltd., 1-5-10, Ebisu-west, Shibuyaku, Tokyo, 150-0021, Japan
* Author to whom correspondence should be addressed.
Received: 21 November 2008; in revised form: 4 January 2009 / Accepted: 8 January 2009 / Published: 16 January 2009
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.
Noguchi Y, Matsumoto F, Maeda K, Nagasawa T. Neural Network Analysis and Evaluation of the Fetal Heart Rate. Algorithms. 2009; 2(1):19-30.
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.