Artificial neural networks applied to cancer detection in a breast screening programme
Artificial neural networks applied to cancer detection in a breast screening programme
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DOI：
10.1016/j.mcm.2010.03.019
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发表时间：
2010-10
期刊：
影响因子：
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通讯作者：
L. Menéndez;F. J. D. C. Juez;F. Lasheras;J. Á. Riesgo
中科院分区：
文献类型：
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作者：
L. Menéndez;F. J. D. C. Juez;F. Lasheras;J. Á. Riesgo
乳腺癌筛查是一种在非常早期阶段检测乳腺癌的方法。第一步是对每个乳房进行X光检查，称为乳房X光检查。乳房X光检查可以发现乳房组织的微小变化，这些变化可能表明癌症太小，以至于妇女自己或医生都感觉不到。世界卫生组织的国际癌症研究机构（IARC）得出结论，乳腺癌的乳房X光检查可以降低死亡率。这意味着，每500名接受筛查的妇女中，就有一人的生命得到挽救。目前的研究使用的信息从1999年至2007年在公共卫生领域的阿维莱斯（阿斯图里亚斯公国，西班牙）进行的乳腺癌筛查计划。阿维莱斯公共卫生区由9个市镇组成，共有160 000名居民。公共卫生领域的选择是基于以下标准：本文描述了一种基于神经网络的乳腺癌诊断方法;开发的模型能够确定哪些女性在接受乳房X光检查之前更有可能患上某种特定类型的肿瘤。
Breast screening is a method of detecting breast cancer at a very early stage. The first step involves taking an X-ray, called a mammogram, of each breast. The mammogram can detect small changes in breast tissue which may indicate cancers which are too small to be felt either by the woman herself or by a doctor. The World Health Organisation’s International Agency for Research on Cancer (IARC) concluded that mammography screening for breast cancer reduces mortality. This means that out of every 500 women screened, one life will be saved. The present research uses the information obtained from the breast screening programme carried out in the public health area of Aviles (Principality of Asturias, Spain) from 1999 to 2007. The public health area of Aviles is formed by nine municipalities with a total of 160,000 inhabitants. The selection of the public health area was based on the following criteria: This paper describes a neural network based approach to breast cancer diagnosis; the model developed is able to determine which women are more likely to suffer from a particular kind of tumour before they undergo a mammography.