IntroductionOxford English Dictionary defines the word "infertile" or barren as "inability to give birth or procreate. " This definition refers to the "sterilization mode rather than visualization difficulty" and presents so many clinical perspectives (1). According to the reports of the International Committee for Monitoring Assisted Reproductive Technology (ICMART) and the World Health Organization (WHO), "infertility" is a couple's failure in pregnancy after 12 months of unprotected sexual intercourse and pregnancy attempts. Infertility is a global problem affecting people around the world whose cause and importance may vary according to the geographical location and socio-economic condition. According to the statistics, annually 60-80 million couples around the world suffer from infertility (2). The estimated fertility rate in Canada is 11.5% to 15.7%. One out of seven English couples suffers from fertility problems (3). The number of couples affected by infertility has increased from 42.0 million people (39.6 million people, 44.8 million people) in 1990 to 48.5 million people (45.0 million people, 52.6 million people) in 2010 (4). Ten to 12% of couples around the world are suffering from infertility in half of which, the man is infertile. The estimates show that in 35%-40% of cases, the man is infertile and in 35%-40% of cases, the woman is infertile and in 20%-30% of cases, it is related to the combination of other factors (5). Infertility occurs once pregnancies are ended up with abortion (ASR) or the delivery of a child with multiple hereditary diseases (6). Infertility diagnosis is different and may include the evaluation of sperm quality; Mormons, and analysis of imaging of uterus and fallopian tubes. According to the medical diagnosis, infertility may be treated by reproductive surgery, prescribing hormones or applying infertility technologies (2). Infertility awareness, like men and women's awareness of risk factors, is the first step in protecting pregnancy in lifestyle modification. Knowledge and awareness of fertility depends on education rather than personal fertility or motherhood and fatherhood experience. Health improving strategies started with educational interventions (3). Secondary infertility refers to a state in which pregnancy does not occur after one year (in some epidemiologic studies 2 years) of unprotected sexual intercourse despite at least one pregnancy in the past. Women with secondary infertility cannot give birth to alive child (7). Infertility may result from a wide range of abnormalities one or both of which exist. However, infertility is not much different in people and it can have a variety of causes (8). The primary and secondary causes of infertility are reviewed in this study. This study examines the following points: primary causes of infertility, such as genetic factors, hormonal disorders, genetic disorders, congenital defects or reproductive system diseases; secondary factors, including lifestyle related factors, such as obesity, diet, smoking, alcohol consumption an...

Data Mining Curriculum: A Proposal (Version 1.0) [2] Diabetes-like renal glomerular disease in Fanconi-Bickel syndrome [3] Data Mining: Concepts and Techniques [4] Infertility Guideline [5] Fertility outcome after IVF and related factors [6] Bayesian classification for the selection of in vitro human embryos using morphological and clinical data [7] The relationship between number of transferred embryos and pregnancy rate in ART cycles [8] Data Mining and Knowledge Discovery [9] Sodium butyrate activates erythroid-specific 5-aminolevulinate synthase gene through Sp1 elements at its promoter [10] A comparison in cluster validation techniques [11] Data Mining: Practical Machine Learning Tools and Techniques [12] Integrating genetic algorithm and decision tree learning for assistance in predicting in vitro fertilization outcomes [13] Case-based reasoning in IVF: Prediction and knowledge mining [14] Factors predicting the cumulative outcome of IVF/ICSI treatment: A multivariable analysis of 2450 patients Aims Intra Uterine Insemination (IUI) is a medically-assisted reproduction technique (ART) enables infertile couples to achieve the successful pregnancy. Given the unpredictability of such techniques, many investigations have been done on the factors affecting the techniques. Data mining is one of the main tools that can help researchers to evaluate the factors. Data mining utilize the statistical methods along with the artificial intelligence (AI) to help different sciences including infertility science and research for interpreting the results and analyzes of data appropriately and extracting the hidden patterns and knowledge in the data. The objective of this study was to analyze the factors affecting IUI results by clustering. Materials & Methods The IUI data were clustered utilizing the K-means)a clustering method in data mining). Davise-Buldian index was used to calculate the best number of clusters. The similar individuals were included in the same cluster and the success rates in those clusters were also measured. Findings Some of the characteristics of individuals such as age, body mass index (BMI), type of infertility, the cause of infertility and etc. were effective factors on IUI success rate. Conclusion Factors such as age, BMI, type of infertility, the cause of infertility and etc. can determine the success rate of the IUI method.