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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Bibliografiset tiedot
Päätekijät: Yueh-Chin Cheng, Yu Hsien Chiu, Hsien-Chang Wang, Fong-Ming Chang, Kao-Chi Chung, Chiung-Hsin Chang, Kuo-Sheng Cheng
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Elsevier 2013-03-01
Sarja:Taiwanese Journal of Obstetrics & Gynecology
Aiheet:
Akaike information criterion
artificial neural network
estimated fetal weight
minimum mean squared error
ultrasonography
Linkit:http://www.sciencedirect.com/science/article/pii/S1028455913000090
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