Analysis of Cardiotocogram Data for Fetal Distress Determination by Decision Tree Based Adaptive Boosting Approach


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.

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Karabulut, E. and Ibrikci, T. (2014) Analysis of Cardiotocogram Data for Fetal Distress Determination by Decision Tree Based Adaptive Boosting Approach. Journal of Computer and Communications, 2, 32-37. doi: 10.4236/jcc.2014.29005.

Conflicts of Interest

The authors declare no conflicts of interest.


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