چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده | نفر چندم مقاله |
|---|---|
| رضا فردوسی | دوم |
| بهناز رائف | اول |
| عنوان | متن |
|---|---|
| خلاصه مقاله | Predictive factore for embryo implantation success rate Background: In spite of recent improvements in infertility treatment, there is no significant increase in pregnancy rates. While the cost and complex process of assisted reproductive technologies (ART) are the main challenging issues. The aim of this study is to predict key factors that could be helpful in select the best embryos to transfer. Materials and Methods: In this study, information of 447 patients and 1154 transferred embryos at day 3, 4 and 5 were collected. Dataset contains 63 variables and a class label, indicating positive and negative implantation outcomes. The relative predictive values of clinical features were assessed using ranking-based algorithms such as Gain ratio and Gini Index in Orange data mining software. Results: The results revealed that, the quality of transferred embryos is the most important predictive factor among examined IVF/ICSI features. Our findings show that the FSH/HMG dosage for ovulation stimulation is the second most important factor in Implantation outcomes. Number of MII quality oocytes and number of blastomeres are other high-ranked features for prediction of the embryo implantation success rate. Conclusion: Elicited decision rules from data mining ranking algorithms offer a clinical decision support tool for selecting the best embryos that lead to improvement in ART success rates. |
| کلمات کلیدی | Assisted Reproductive Technologies, Data Mining, Ranking Algorithms, Clinical Decision Suppor |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| Predictive factore for embryo implantation success rate.pdf | 1398/02/31 | 1028036 | دانلود |
| Raef 19.pdf | 1398/02/30 | 1558786 | دانلود |
