An Intelligent Model for Prediction of In-Vitro Fertilization Success using MLP Neural Network and GA Optimization

Feli, E.; Hosseini, R.; Yazdani, S.

doi:10.22044/jadm.2021.10718.2208

Document Type : Technical Paper

Authors

¹ Department of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran.

² Department of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran.

https://doi.org/10.22044/jadm.2021.10718.2208

Abstract

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.

Keywords

20.1001.1.23225211.2021.9.4.9.6

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Journal of AI and Data Mining

An Intelligent Model for Prediction of In-Vitro Fertilization Success using MLP Neural Network and GA Optimization

References

References

Volume 9, Issue 4
November 2021
Pages 515-523

An Intelligent Model for Prediction of In-Vitro Fertilization Success using MLP Neural Network and GA Optimization

References

References

Volume 9, Issue 4November 2021Pages 515-523

Volume 9, Issue 4
November 2021
Pages 515-523