Abstract
BackgroundTo evaluate the use of artificial intelligence (AI) in predicting the success rate of intrauterine insemination (IUI) treatment among infertile couples and also to determine the importance of each of the parameters affecting IUI success. This study was a retrospective cohort study in which information from 380 infertile couples undergoing IUI treatment (190 cases resulting in positive pregnancy test and 190 cases of failed IUI) including underlying factors, female factors, sperm parameters at the beginning of the treatment cycle, and fertility results were collected from 2013 to 2019 and evaluated to determine the effectiveness of AI in predicting IUI success.ResultsWe used the most important factors influencing the success of IUI as a neural network input. With the help of a three-layer neural network, the accuracy of the AI to predict the success rate of IUI was 71.92% and the sensitivity and specificity were 76.19% and 66.67%, respectively. The effect of each of the predictive factors was obtained by calculating the ROC curve and determining the cut-off point.ConclusionsThe morphology, total motility, and progressive motility of the sperm were found to be the most important predictive factors for IUI success. In this study, we concluded that by predicting IUI success rate, artificial intelligence can help clinicians choose individualized treatment for infertile couples and to shorten the time to pregnancy.
Highlights
To evaluate the use of artificial intelligence (AI) in predicting the success rate of intrauterine insemination (IUI) treatment among infertile couples and to determine the importance of each of the parameters affecting IUI success
Among the methods used in the treatment of infertility is the intrauterine insemination (IUI), which is used in the treatment of infertility with male, cervical, ovarian, and immunological factors and infertility with unexplained etiologies, which account for about 40% of infertility causes [6]
The designed network accuracy was best achieved with 14 neurons in Parameter Female age Female body mass index (BMI) follicle-stimulating hormone (FSH) (IU/L) AMH Male age Sperm count Parameter Total sperm motility Sperm progressive motility Sperm morphology
Summary
To evaluate the use of artificial intelligence (AI) in predicting the success rate of intrauterine insemination (IUI) treatment among infertile couples and to determine the importance of each of the parameters affecting IUI success. Among the methods used in the treatment of infertility is the intrauterine insemination (IUI), which is used in the treatment of infertility with male, cervical, ovarian, and immunological factors and infertility with unexplained etiologies, which account for about 40% of infertility causes [6]. This is a cheap, easy to use, and a relatively non-invasive method compared to other methods of infertility treatment, but a wide success rate for this method has been reported in different studies [7]. Choosing the right treatment protocol and predicting the results of assisted reproduction can significantly reduce these costs and help infertility professionals
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