Using Akaike information criterion and minimum mean square error mode in compensating for ultrasonographic errors for estimation of fetal weight by new operators

Using Akaike information criterion and minimum mean square error mode in compensating for ultrasonographic errors for estimation of fetal weight by new operators

Objectives: The accuracy of ultrasound (US) measurements is operator dependent. In order to decrease the operator-dependent errors in estimated fetal weight (EFW), a model selection analysis was undertaken to select significant compensation weighting factors on ultrasonographic parameters to support...

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Bibliographic Details
Main Authors:	Yueh-Chin Cheng, Yu Hsien Chiu, Hsien-Chang Wang, Fong-Ming Chang, Kao-Chi Chung, Chiung-Hsin Chang, Kuo-Sheng Cheng
Format:	Article
Language:	English
Published:	Elsevier 2013-03-01
Series:	Taiwanese Journal of Obstetrics & Gynecology
Subjects:	Akaike information criterion artificial neural network estimated fetal weight minimum mean squared error ultrasonography
Online Access:	http://www.sciencedirect.com/science/article/pii/S1028455913000090

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