Volume 2, Issue 2 (2017)                   SJMR 2017, 2(2): 105-112 | Back to browse issues page

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Alizadeh S, Asghari M, Hosseini M. Analysis of the Factors on Intrauterine Insemination (IUI) Results by Clustering. SJMR 2017; 2 (2) :105-112
URL: http://saremjrm.com/article-1-37-en.html
Analysis of the Factors on Intrauterine Insemination (IUI) Results by Clustering
S. Alizadeh1 , M. Asghari *2 , M.K. Hosseini1
1- Information Technology Department, Computer Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran
2- Information Technology Department, Computer Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran , mohsen.asghari@gmail.com
Abstract:   (6837 Views)

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 and 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.

Keywords: Infertility, Insemination, Artificial, Clustering, Data Mining
Full-Text [PDF 540 kb]   (2312 Downloads)    
Article Type: Original Research | Subject: Sterility
Received: 2016/02/26 | Accepted: 2016/06/21 | Published: 2017/08/16
English Expanded Abstract [HTML 21 KB]  (113 Download)
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