Paper Title :Estimation of APGAR Scoring by Artificial Neural Networks
Author :Baris Doruk Gungor, Mehmet Recepbozkurt
Article Citation :Baris Doruk Gungor ,Mehmet Recepbozkurt ,
(2018 ) " Estimation of APGAR Scoring by Artificial Neural Networks " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 7-9,
Volume-6, Issue-12
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.
Type : Research paper
Published : Volume-6, Issue-12
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-14433
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Copyright: © Institute of Research and Journals
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Published on 2019-02-21 |
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