Development of Data Mining Model for InVitro Fertilization Data Retrieval

Abstract

Urbanisation and transition in lifestyle are leading to increase in infertility rates in India. To deal with the problem of infertility, there exists various methods such as In Vitro Fertilization (IVF), Gamete Intrafallopian Transfer (GIFT), Zygote Intrafallopian Transfer (ZIFT), Frozen Embryo Transfer (FET) etc. Among these existing methods, IVF is most widely used method. But, before suggesting IVF procedure, doctors need to predict success rate. Hence, IVF success rate prediction is gaining importance because of the current scenario. newlineTechnology can assist the IVF success rate prediction. Recent developments in the computing field like development of machine learning (ML) models is promising. These algorithms can be applied to any field and utilized as required. Usage of machine learning algorithms has gained momentum in medical field in recent days. This includes usage of algorithms for success rate prediction of IVF methods. As multiple intrinsic and extrinsic factors are to be analysed before suggesting IVF procedure, researchers have proposed various methods to improve the accuracy of prediction. But, there exists a lot of scope to improve these prediction accuracies by applying multiple machine learning methods.