TITLE:
Analysis of Cardiotocogram Data for Fetal Distress Determination by Decision Tree Based Adaptive Boosting Approach
AUTHORS:
Esra Mahsereci Karabulut, Turgay Ibrikci
KEYWORDS:
Cardiotocogram, Fetal Distress, Adaptive Boosting, Decision Tree
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.9,
July
11,
2014
ABSTRACT: Cardiotocography is one
of the most widely used technique for recording changes in fetal heart rate
(FHR) and uterine contractions. Assessing cardiotocography is crucial in that
it leads to iden- tifying fetuses which suffer from lack of oxygen, i.e. hypoxia.
This situation is defined as fetal dis- tress and requires fetal intervention
in order to prevent fetus death or other neurological disease caused by
hypoxia. In this study a computer-based approach for analyzing cardiotocogram
in- cluding diagnostic features for discriminating a pathologic fetus. In order
to achieve this aim adaptive boosting ensemble of decision trees and various
other machine learning algorithms are employed.