Literature DB >> 7569751

Application of neural networks to the ranking of perinatal variables influencing birthweight.

R J Lapeer1, K J Dalton, R W Prager, J J Forsström, H K Selbmann, R Derom.   

Abstract

In this paper we compare Multi-Layer Perceptrons (a neural network type) with Multivariate Linear Regression in predicting birthweight from nine perinatal variables which are thought to be related. Results show, that seven of the nine variables, i.e., gestational age, mother's body-mass index (BMI), sex of the baby, mother's height, smoking, parity and gravidity, are related to birthweight. We found no significant relationship between birthweight and each of the two variables, i.e., maternal age and social class.

Mesh:

Year:  1995        PMID: 7569751     DOI: 10.3109/00365519509088454

Source DB:  PubMed          Journal:  Scand J Clin Lab Invest Suppl        ISSN: 0085-591X


  1 in total

1.  (1)H NMR- based metabolomics approaches as non- invasive tools for diagnosis of endometriosis.

Authors:  Negar Ghazi; Mohammad Arjmand; Ziba Akbari; Ali Owsat Mellati; Hamid Saheb-Kashaf; Zahra Zamani
Journal:  Int J Reprod Biomed (Yazd)       Date:  2016-01
  1 in total

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