期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2011
卷号：2
期号：3(Version 1)
出版社：Ayushmaan Technologies
摘要：A binary Discrete Particle Swarm Optimization;BPSO/DPSO was proposed and successfully applied to the classification risk of Wisconsin-breast-cancer data set. Breast cancer is one of the leading causes of death among the women in many parts of the world. In 2007, approximately 178,480 women in the United States will be found to have invasive breast cancer. However, the medical technology has been improved and causing declination of the mortality in breast cancer in the past decade. This has been possible owing to earlier diagnosis and improved treatment. Hence, the purpose of this study was to separate from a population of patients who had and had not breast cancer. This study proposed the methodology for data mining that the fundamental of concept was in terms of the standard PSO called Discrete PSO. The novel PSO in which each particle was coded in positive integer numbers and has a feasible system structure. Based on the obtained results, our research used the two rules to improve the accuracy to 96.995%, sensitivity to 100% and specificity to 95.83%. The results compared with the previous research that showed the improvement of accuracy at the same number of rules. In this research we have got high quality results which can be used as reference for hospital decision making and research workers.s for
关键词：Discrete Particle Swarm Optimization; Breast Cancer; Data;Mining...r.n.
