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Use of General Regression Artificial Neural Network to Identify the Natural Growth of Head Circumference of the Baby
Author(s) -
Susan Mohammed,
Aesha Shaheen,
Amera Ismail Melhum
Publication year - 2013
Publication title -
maǧallaẗ al-rāfidayn li-ʿulūm al-ḥāsibāt wa-al-riyāḍiyyāẗ/˜al-œrafidain journal for computer sciences and mathematics
Language(s) - English
Resource type - Journals
eISSN - 2311-7990
pISSN - 1815-4816
DOI - 10.33899/csmj.2013.163423
Subject(s) - head circumference , circumference , head (geology) , natural (archaeology) , medicine , sign (mathematics) , statistics , artificial neural network , demography , pediatrics , mathematics , computer science , artificial intelligence , geography , birth weight , biology , geometry , sociology , mathematical analysis , pregnancy , genetics , paleontology , archaeology
Recently, many cases of deformities and health problems that affect the newborn were recorded, because of the known pollutants and radiation. One of these problems is the growth of the child, both in terms of height and weight or in terms of the natural growth of head circumference. Any increase or decrease in the measurement of head circumference a sign of a problem This research addresses the issue of natural growth of the baby's head circumference from the first month until he/she reaches a year and half old. Artificial neural networks were used to train the normal values for the growth of head circumference based on the medical chart for the growth of head circumference and adopted internationally. Results showed the efficiency and accuracy of the work of these networks in the diagnosis of natural cases from the others.

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