Knowledge discovery on in vitro fertilization clinical data using particle swarm optimization

Chih Chuan Chen, Yi Chung Cheng, Chao Chin Hsu, Sheng Tun Li

研究成果: Conference contribution

8 引文 斯高帕斯(Scopus)

摘要

In vitro fertilization (IVF) is a medically assisted reproduction technique (ART) for treating infertility. During IVF procedures, a female patient requires hormone treatment to control ovulation, oocytes are taken from the patient and fertilized in vitro, and after fertilization, one or usually more resulting embryos are transferred into the uterus. Although IVF is considered as a method of last resort for infertile couples, the success rate is still low, which can be only as high as 40% for women under age of 30. In this study, we build a predictive model which takes into account a patient's physiology and the results of the stages of an IVF cycle, to assist obstetricians and gynecologists in increasing success rate of IVF. The predictive model is based on a knowledge discovering technique incorporated with particle swarm optimization (PSO), which is a competitive heuristic technique for solving optimization task. This study uses the database of IVF cycles developed by a women and infants clinic in Taiwan as the foundation. A repertory grid is developed to help selecting attributes for the data mining technique. The results show that the proposed technique can exploit rules approved by the obstetrician/gynecologist and the assistant on both comprehensibility and justifiability.

原文English
主出版物標題Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
頁面278-283
頁數6
DOIs
出版狀態Published - 2009
事件2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009 - Taichung, Taiwan
持續時間: 2009 6月 222009 6月 24

出版系列

名字Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009

Other

Other2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
國家/地區Taiwan
城市Taichung
期間09-06-2209-06-24

All Science Journal Classification (ASJC) codes

  • 資訊系統
  • 生物醫學工程
  • 健康資訊學

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