Ultrasound estimation of fetal weight in twins by artificial neural network

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), abdominal diameter (AD), biparietal diameter (BPD). Then, a total of 121 twin fetuses were assessed subsequently as the validation group. In validation group, the mean absolute error and the mean absolute percent 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.