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Journal of Obstetrics, Gynecology and Cancer Research، جلد ۳، شماره ۴، صفحات ۰-۰
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Prediction of Clinical Pregnancy Occurrence After ICSI using Decision Tree and Support Vector Machine Methods |
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| چکیده انگلیسی مقاله |
Background and Objective: Studies have shown that despite the numerous research carried out regarding infertility treatment, there is still a long way to treat this diseasesatisfactorily. Spending a lot of time and money on infertility treatments proves the necessity of designing a model which could predict the result of treatment methods with an acceptable accuracy; a model that could help physicians to get rid of trial and error for treatment methods which should step by step be applied on an infertile couple. Intracytoplasmic Sperm Injectionis one of the assisted reproductive techniques. Statistics have indicated that the probability of pregnancy occurrence is only about 30% using this method. In this paper, a model which could predict the result ofIntracytoplasmic Sperm Injection was presented using the decision tree and support vector machine methods. Methods: The applied data were collected in seven months from December 2012 to June 2013 by analyzing 251 treatment cycles in Omid Fertility Clinic. Input variables of the model were parameters like couple's medical records, hormonal tests, the cause of infertility, and the like. The output variable was the occurrence or nonoccurrence of the clinical pregnancy (the pregnancy resulting in the formation of the fetal heart). One of the innovations of this study was that the input variables of the model were only preoperative, while in previous studies, having information about some of the surgery stages, such as quality of the egg and the like, was required to anticipate the result of the surgery. Results: The obtained accuracy using the decision tree and support vector machine methods were 70.3% and75.7%, respectively. Conclusion:The results of the current study demonstrated that the support vector machine method had a better performance compared to the decision tree method. Presented model predictsthe occurrence or nonoccurrence of a clinical pregnancy follows Intracytoplasmic Sperm Injection, with a precision of 75.7%. |
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| کلیدواژه‌های انگلیسی مقاله |
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| نویسندگان مقاله |
| Mahdieh Kafaee Ghaeini
MSc student of Industrial Engineering-System Management, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
| M. R. Amin-Naseri
Professor, Industrial and Systems Engineering,Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
| Marzieh Aghahoseini
Professor of Medical School, Tehran University of Medical Sciences, Tehran, Iran
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| نشانی اینترنتی |
http://jogcr.com/browse.php?a_code=A-10-72-1&slc_lang=en&sid=1 |
| فایل مقاله |
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| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
عمومی |
| نوع مقاله منتشر شده |
پژوهشی اصیل |
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