Prediction of fetal weight based on back propagation neural network optimized by genetic algorithm-Reference-Cited by-同舟云学术

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Prediction of fetal weight based on back propagation neural network optimized by genetic algorithm

Published:2021 Issue:4 Volume:18 Page:4402-4410
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:
Short-container-title:MBE

Author:

Gao Hong, ,Wu Cuiyun,Huang Dunnian,Zha Dahui,Zhou Cuiping

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

Reference22 articles.

1. C. Bo, Y. Jie, G. E, F. Chuan, Z. Long, A method for estimating fetal weight based on body composition, J. Matern. Fetal. Neonatal. Med., 32 (2019), 3306-3314.

2. X. G. Hua, W. Jiang, R. Hu, C. Y. Hu, K. Huang, F. L. Li, et al., Large for gestational age and macrosomia in pregnancies without gestational diabetes mellitus, J. Matern. Fetal. Neonatal. Med., 33 (2020), 3549-3558.

3. S. Turkmen, S. Johansson, M. Dahmoun, Foetal macrosomia and foetal-maternal outcomes at birth, J. Pregnancy, 2018 (2018), 4790136.

4. M. J. Shepard, V. A. Richards, R. L. Berkowitz, S. L. Warsof, J. C. Hobbins, An evaluation of two equations for predicting fetal weight by ultrasound, Am. J. Obstet. Gynecol., 142 (1982), 47-54.

5. F. P. Hadlock, R. B. Harrist, R. J. Carpenter, R. L. Deter, S. K. Park, Sonographic estimation of fetal weight. The value of femur length in addition to head and abdomen measurements, Radiology, 150 (1984), 535-540.

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