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A Study of Artificial Neural Network Training Algorithms for Classification of Cardiotocography Signals
2017
Bitlis Eren University Journal of Science and Technology
A B S T R A C T Cardiotocography (CTG) containing of fetal heart rate (FHR) and uterine contraction (UC) signals is a monitoring technique. During the last decades, FHR signals have been classified as normal, suspicious, and pathological using machine learning techniques. As a classifier, artificial neural network (ANN) is notable due to its powerful capabilities. For this reason, behaviors and performances of neural network training algorithms were investigated and compared on classification
doi:10.17678/beuscitech.338085
fatcat:yaymo652lrehbangkerbpinvja