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A Software Tool for Determination of Breast Cancer Treatment Methods Using Data Mining Approach

机译:使用数据挖掘方法确定乳腺癌治疗方法的软件工具

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摘要

In this work, breast cancer treatment methods are determined using data mining. For this purpose, software is developed to help to oncology doctor for the suggestion of application of the treatment methods about breast cancer patients. 462 breast cancer patient data, obtained from Ankara Oncology Hospital, are used to determine treatment methods for new patients. This dataset is processed with Weka data mining tool. Classification algorithms are applied one by one for this dataset and results are compared to find proper treatment method. Developed software program called as “Treatment Assistant” uses different algorithms (IB1, Multilayer Perception and Decision Table) to find out which one is giving better result for each attribute to predict and by using Java Net beans interface. Treatment methods are determined for the post surgical operation of breast cancer patients using this developed software tool. At modeling step of data mining process, different Weka algorithms are used for output attributes. For hormonotherapy output IB1, for tamoxifen and radiotherapy outputs Multilayer Perceptron and for the chemotherapy output decision table algorithm shows best accuracy performance compare to each other. In conclusion, this work shows that data mining approach can be a useful tool for medical applications particularly at the treatment decision step. Data mining helps to the doctor to decide in a short time.
机译:在这项工作中,使用数据挖掘确定乳腺癌的治疗方法。为此,开发了可帮助肿瘤医生建议应用乳腺癌患者治疗方法的软件。从安卡拉肿瘤医院获得的462位乳腺癌患者数据用于确定新患者的治疗方法。该数据集使用Weka数据挖掘工具进行处理。对该数据集一一应用分类算法,并比较结果以找到合适的处理方法。开发的软件程序称为“ Treatment Assistant”,它使用不同的算法(IB1,多层感知和决策表)来找出哪种方法可以通过Java Net bean接口为每个属性提供更好的预测结果。使用此开发的软件工具,可以确定乳腺癌患者术后的治疗方法。在数据挖掘过程的建模步骤中,将不同的Weka算法用于输出属性。对于激素疗法输出IB1,对于他莫昔芬和放射疗法输出,多层感知器以及对于化学疗法输出,决策表算法相互比较显示出最佳的准确性。总之,这项工作表明,数据挖掘方法可以成为医疗应用的有用工具,尤其是在治疗决策步骤。数据挖掘有助于医生在短时间内做出决定。

著录项

  • 来源
    《Journal of Medical Systems》 |2011年第6期|p.1503-1511|共9页
  • 作者单位

    Department of Electronics-Computer Education, Faculty of Technical Education, Süleyman Demirel University, Isparta, Turkey;

    Department of Electronics-Computer Education, Faculty of Technical Education, Süleyman Demirel University, Isparta, Turkey;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Breast cancer; Data mining; Weka;

    机译:乳腺癌;数据挖掘;Weka;

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