Dubey Ashutosh Kumar, Gupta Umesh, Jain Sonal
Department of Computer Science and Engineering, JK Lakshmipat University, Jaipur, India E-mail :
Asian Pac J Cancer Prev. 2015;16(10):4237-45. doi: 10.7314/apjcp.2015.16.10.4237.
Breast cancer is a menacing cancer, primarily affecting women. Continuous research is going on for detecting breast cancer in the early stage as the possibility of cure in early stages is bright. There are two main objectives of this current study, first establish statistics for breast cancer and second to find methodologies which can be helpful in the early stage detection of the breast cancer based on previous studies. The breast cancer statistics for incidence and mortality of the UK, US, India and Egypt were considered for this study. The finding of this study proved that the overall mortality rates of the UK and US have been improved because of awareness, improved medical technology and screening, but in case of India and Egypt the condition is less positive because of lack of awareness. The methodological findings of this study suggest a combined framework based on data mining and evolutionary algorithms. It provides a strong bridge in improving the classification and detection accuracy of breast cancer data.
乳腺癌是一种危险的癌症，主要影响女性。由于早期治愈的可能性很大，目前正在持续进行乳腺癌早期检测的研究。本研究有两个主要目标，一是建立乳腺癌统计数据，二是根据以往研究找到有助于乳腺癌早期检测的方法。本研究考虑了英国、美国、印度和埃及的乳腺癌发病率和死亡率统计数据。该研究结果证明，由于意识提高、医疗技术改进和筛查，英国和美国的总体死亡率有所改善，但在印度和埃及，由于意识缺乏，情况不太乐观。本研究的方法学结果提出了一个基于数据挖掘和进化算法的组合框架。它为提高乳腺癌数据的分类和检测准确性提供了一座强有力的桥梁。
