An Intelligent Model for Prediction of In-Vitro Fertilization Success using MLP Neural Network and GA Optimization | ||
| Journal of AI and Data Mining | ||
| دوره 9، شماره 4، بهمن 2021، صفحه 515-523 اصل مقاله (1.29 M) | ||
| نوع مقاله: Technical Paper | ||
| شناسه دیجیتال (DOI): 10.22044/jadm.2021.10718.2208 | ||
| نویسندگان | ||
| E. Feli1؛ R. Hosseini* 2؛ S. Yazdani1 | ||
| 1Department of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran. | ||
| 2Department of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran. | ||
| چکیده | ||
| In Vitro Fertilization (IVF) is one of the scientifically known methods of infertility treatment. This study aimed at improving the performance of predicting the success of IVF using machine learning and its optimization through evolutionary algorithms. The Multilayer Perceptron Neural Network (MLP) were proposed to classify the infertility dataset. The Genetic algorithm was used to improve the performance of the Multilayer Perceptron Neural Network model. The proposed model was applied to a dataset including 594 eggs from 94 patients undergoing IVF, of which 318 were of good quality embryos and 276 were of lower quality embryos. For performance evaluation of the MLP model, an ROC curve analysis was conducted, and 10-fold cross-validation performed. The results revealed that this intelligent model has high efficiency with an accuracy of 96% for Multi-layer Perceptron neural network, which is promising compared to counterparts methods. | ||
| کلیدواژهها | ||
| Multilayer Perceptron neural network؛ Genetic Algorithm؛ Predicting the success of IVF | ||
| مراجع | ||
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