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Mostaar, A, Sattari, M R, Hosseini, S, Deevband, M R. (1398). Use of Artificial Neural Networks and PCA to Predict Results of Infertility Treatment in the ICSI Method. سامانه مدیریت نشریات علمی, 9(6), 679-386. doi: 10.31661/jbpe.v0i0.1187
A Mostaar; M R Sattari; S Hosseini; M R Deevband. "Use of Artificial Neural Networks and PCA to Predict Results of Infertility Treatment in the ICSI Method". سامانه مدیریت نشریات علمی, 9, 6, 1398, 679-386. doi: 10.31661/jbpe.v0i0.1187
Mostaar, A, Sattari, M R, Hosseini, S, Deevband, M R. (1398). 'Use of Artificial Neural Networks and PCA to Predict Results of Infertility Treatment in the ICSI Method', سامانه مدیریت نشریات علمی, 9(6), pp. 679-386. doi: 10.31661/jbpe.v0i0.1187
Mostaar, A, Sattari, M R, Hosseini, S, Deevband, M R. Use of Artificial Neural Networks and PCA to Predict Results of Infertility Treatment in the ICSI Method. سامانه مدیریت نشریات علمی, 1398; 9(6): 679-386. doi: 10.31661/jbpe.v0i0.1187

Use of Artificial Neural Networks and PCA to Predict Results of Infertility Treatment in the ICSI Method

Journal of Biomedical Physics and Engineering
مقاله 12، دوره 9، شماره 6، بهمن و اسفند 2019، صفحه 679-386    اصل مقاله (889.66 K)
نوع مقاله: Original Research
شناسه دیجیتال (DOI): 10.31661/jbpe.v0i0.1187
نویسندگان
A Mostaar* 1، 2؛ M R Sattari3؛ S Hosseini4؛ M R Deevband1
1PhD, Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2PhD, Radiation Biology Research Center, Iran University of Medical Sciences, Tehran, Iran
3MSc, Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4PhD, Preventive Gynecology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
چکیده
Background: Intracytoplasmic sperm injection (ICSI) or microinjection is one of the most commonly used assisted reproductive technologies (ART) in the treatment of patients with infertility problems. At each stage of this treatment cycle, many dependent and independent variables may affect the results, according to which, estimating the accuracy of fertility rate for physicians will be difficult.
Objective: This study aims to evaluate the efficiency of artificial neural networks (ANN) and principal component analysis (PCA) to predict results of infertility treatment in the ICSI method.
Material and Methods: In the present research that is an analytical study, multilayer perceptron (MLP) artificial neural networks were designed and evaluated to predict results of infertility treatment using the ICSI method. In addition, the PCA method was used before the process of training the neural network for extracting information from data and improving the efficiency of generated models. The network has 11 to 17 inputs and 2 outputs.
Results: The area under ROC curve (AUC) values were derived from modeling the results of the ICSI technique for the test data and the total data. The AUC for total data vary from 0.7670 to 0.9796 for two neurons, 0.9394 to 0.9990 for three neurons and 0.9540 to 0.9906 for four neurons in hidden layers.
Conclusion: The proposed MLP neural network can model the specialist performance in predicting treatment results with a high degree of accuracy and reliability.
کلیدواژه‌ها
Neural Networks؛ Principal Component Analysis؛ Fertility؛ Intracytoplasmic Sperm Injection
مراجع
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