Ultrasound estimation of fetal weight in twins by artificial neural network

Hanieh Mohammadi, Meshkat Nemati, Zohreh Allahmoradi, Hoda Forghani Raissi, Somayeh Saraf Esmaili, Ali Sheikhani

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DOI: 10.4236/jbise.2011.41006                

Abstract

This study was undertaken to determine the accuracy of using Ultrasound (US) estimation of twin fetuses by use of Artificial Neural Network. At First, as the training group, we performed US examinations on 186 healthy singleton fetuses within 3 days of delivery. Three input variables were used to construct the ANN model: abdominal circumference (AC), ab-dominal diameter (AD), biparietal diameter (BPD). Then, a total of 121 twin fetuses were assessed sub-sequently as the validation group. In validation group, the mean absolute error and the mean absolute per-cent error between estimated fetal weight and actual fetal weight was 261.77 g and 7.81%, respectively. Results show that, twin estimation of birth weight by ultrasound correlates fairly well with the actual weights of twin fetuses.

Keywords

Ultrasound; Fetal Weight Estimation; Twin; Artificial Neural Network

Conflicts of Interest

The authors declare no conflicts of interest.

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