Abstract
The rapid development of information technologies enables successful results in computer-aided studies. This has led researchers to investigate the usability of technologies such as computer and software supported systems, machine learning, and artificial intelligence in many studies. One of these areas is health. For example, in order not to risk the condition of the mother and baby, in some cases, it is very important to correctly determine the times when the cesarean operation, which is mandatory, is mandatory. In this context, in order to make a faster and more accurate decision, it is very important to determine which attributes and how important the level is in making obligatory cesarean. In this study, to determine whether or not caesarean is necessary in the literature, the importance level of the five criteria taken into consideration has been determined and an attribute determination has been carried out and then a classification has been made. Although the same data set was previously classified with different methods, no study was found on determining the significance levels of the attributes and using artificial neural networks as a method. For this reason, in this study, the feature was determined using an adaptive nerve-fuzzy classifier and classified using artificial neural networks. When the results are examined, it is concluded that the importance levels of the attributes are different. Although the values such as accuricy, Sensitivity, and Specificity calculated to evaluate the classification results were found to be quite high for the training set, it was observed that the desired success was not achieved in the test data. While this result is promising, it also reveals the need to increase the learning performed with larger data sets.
Highlights
Today, with the developing technology, the amount of data increases day by day
Adaptive nerve-fuzzy classifier was used for determining the significance levels of the features and the feature selection, and Artificial neural networks were used for classification
When we look at the literature, it is seen that Artificial Neural Network (ANN) is used in many fields such as medical and health applications, industrial applications, military and defense applications, and financial applications
Summary
With the developing technology, the amount of data increases day by day. The need to extract meaningful information between these increased data caused many concepts such as data mining. When the literature is analyzed, it is seen that the feature selection is used in studies in many areas. The studies in the literature with the same data set are as follows; Gharehchopogh and his colleagues have worked on predicting situations where cesarean is required. Amin and Ali evaluated the performance of some methods used in data mining on cesarean data. The methods they use are random forest, logistic regression, naive bayes, k-nearest neighbors, and support vector machine. No study with Artificial Neural Network (ANN) was found in the data set analyzed by different methods. The evaluation of the same data set from different angles will contribute to the literature
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