Fetal distress prediction using discriminant analysis, decision tree, and artificial neural network
Fetal distress prediction using discriminant analysis, decision tree, and artificial neural network作者机构：Department of Industrial Engineering & Management National Chin-Yi University of Technology Taichung Chinese Taipei
出 版 物：《Journal of Biomedical Science and Engineering》 (生物医学工程（英文）)
年 卷 期：2012年第5卷第9期
页 面：526-533页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Fetal Distress Cardiotocography (CTG) Discriminant Analysis Decision Tree Artificial Neural Network
摘 要：Fetal distress is one of the main factors to cesarean section in obstetrics and gynecology. If the fetus lack of oxygen in uterus, threat to the fetal health and fetal death could happen. Cardiotocography (CTG) is the most widely used technique to monitor the fetal health and fetal heart rate (FHR) is an important index to identify occurs of fetal distress. This study is to propose discriminant analysis (DA), decision tree (DT), and artificial neural network (ANN) to evaluate fetal distress. The results show that the accuracies of DA, DT and ANN are 82.1%, 86.36% and 97.78%, respectively.
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