Application of Artificial Intelligence Algorithms to Estimate the Success Rate in Medically Assisted Procreation

Fernando Luís Ferreira,Beatriz Brás De Guimarães,Pedro Ferreira,José Luís Metello,José Manuel Fonseca,Leonardo Martins

doi:10.3390/reprodmed1030014

Abstract

The aim of this study was to build an Artificial Neural Network (ANN) complemented by a decision tree to predict the chance of live birth after an In Vitro Fertilization (IVF)/Intracytoplasmic Sperm Injection (ICSI) treatment, before the first embryo transfer, using demographic and clinical data. Overall, 26 demographic and clinical data from 1193 cycles who underwent an IVF/ICSI treatment at Centro de Infertilidade e Reprodução Medicamente Assistida, between 2012 and 2019, were analyzed. An ANN was constructed by selecting experimentally the input variables which most correlated to the target through Pearson correlation. The final used variables were: woman’s age, total dose of gonadotropin, number of eggs, number of embryos and Antral Follicle Count (AFC). A decision tree was developed considering as an initial set the input variables integrated in the previous model. The ANN model was validated by the holdout method and the decision tree model by the 10-fold cross method. The ANN accuracy was 75.0% and the Area Under the Receiver Operating Characteristic (AUROC) curve was 75.2% (95% Confidence Interval (CI): 72.5–77.5%), whereas the decision tree model reached 75.0% and 74.9% (95% CI: 72.3–77.5%). These results demonstrated that both ANN and decision tree methods are fair for prediction the chance of conceive after an IVF/ICSI cycle.

Highlights

Infertility is a global health issue that afflicts around 15% of couples worldwide [1]
In 1997, Kaufmann et al [18] constructed a neural network, achieving an accuracy of 59.0% while only using four inputs
The aim of the current work was to model the success rate of In Vitro Fertilization (IVF)/Intracytoplasmic Sperm Injection (ICSI) treatment, supporting physicians in patient counselling in a daily basis and helping couples to understand their chances on having a live birth

Summary

Introduction

Infertility is a global health issue that afflicts around 15% of couples worldwide [1]. The causes of infertility are multiple and both men and women may be affected. In about 30% of cases, both contribute to the problem while in around 10% it is not possible to establish a definitive cause [5]. IVF/ICSI treatments are the last solution for many couples, but they come with several drawbacks, such as being expensive, emotionally burdensome, with secondary effects and with a variable likelihood of success. This issue is important to deal with the couples’ expectations, and to prepare institutions when public funding is applied. Costs and effectiveness continue to stimulate discussion in scientific and public forums [6]

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