International Journal of Advance Computational Engineering and Networking (IJACEN)
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Volume-7,Issue-12  ( Dec, 2019 )
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Statistics report
Feb. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 83
Paper Published : 1216
No. of Authors : 3056
  Journal Paper

Paper Title
Estimation of APGAR Scoring by Artificial Neural Networks

Abstract
To determine the effect of obstetric anesthesia on infants, It was developed in 1953 by Virginia Apgar. It is also an important method in terms of neurological development as far as the baby’s physical health is concerned. This method, which consists of 5 criteria, is used in the evaluation of the fetal condition, nst, cst, oct, amniotic fluid index, doppler, umbilical cord and cord blood gas analysis methods, as well as Apgar Score, are frequently used. In this study, maternal and fetal physiological data and attributes extracted from FHR (fetal heart rate) and UC (uterine contraction) signals were examined for a prenatal determination whether an intervention was needed for newborn baby and studies were made for Apgar Scoring. Keywords: Apgar Score, Cardiotocography, Neural Networks, SPSS Analysis, Mann-Whitney U Test.


Author - Baris Doruk Gungor, Mehmet Recepbozkurt

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| Published on 2019-02-21
   
   
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