Infertility is a major concern in health sciences. Many treatment strategies
are being developed to overcome this problem. Assisted reproductive technologies
(ART) are used in the treatment of infertility. Depending on the cause of infertility,
different approaches can be applied in the field of ART treatments. However, since
infertility is complex, it may be difficult to select the best treatment strategy for each
patient. Mathematical modeling is used to understand better and sometimes even
predict a pattern and outcome of biological processes. Thus, developing models help
scientists and medical doctors select the best way of treatment and improve pregnancy
rates. To date, a number of mathematical model systems have been tested to classify
different parameters in infertile patients to develop a model that can predict the chances
of becoming pregnant by identifying the behavioral design. In this chapter, several
mathematical models are reviewed that corroborate the data obtained from infertile
patients and predict the outcome depending on different parameters, including female
age, follicle size, and hormonal levels.
Keywords: Assisted Reproductive Technologies (ART), Fuzzy Logic, Hormonal
Levels, Infertility, Mathematical Modeling, Prediction in Pregnancy Rate,
Pregnancy Calculation, Reproduction.
