利用机器学习分析导致癌症发展的基因

Geetika Aggarwal, Sarika Jain
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引用次数: 2

摘要

成年人的身体平均由大约37万亿个细胞组成。我们身体里的健康细胞在我们的一生中以一种可控的方式分裂和替换自己。但是,当健康细胞不受控制地分裂时,它们会形成新的、不正常的细胞,从而在受影响的身体部位造成损伤。这种病变可以是癌性的,也可以是非癌性的。在哪个阶段了解癌症肿瘤是至关重要的,因为这将决定治疗的基础。在本文中,我们提到了癌症的基础知识,并使用不同的数据挖掘算法来检测乳腺癌。在我们提出的研究工作中,使用WEKA软件进行十次交叉验证来计算和积累结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Genes Responsible for the Development of Cancer using Machine Learning
The average adult human's body is made up of approximately 37 trillion cells. Healthy cells in our bodies divide and replace themselves in a controlled fashion throughout our lives. But when healthy cells divide uncontrollably, they form new, abnormal cells, thus making a lesion in an affected body part. This lesion can be cancerous or non-cancerous. At what stage one got to know about the cancerous tumour is crucial as that would decide the basis of treatment. In this paper, we mentioned the basics of cancer and used different algorithms of data mining to detect breast cancer. In our proposed research work, WEKA software is applied with ten cross validation to calculate and accumulate result.
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