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一种使用数据挖掘方法确定乳腺癌治疗方法的软件工具。

A software tool for determination of breast cancer treatment methods using data mining approach.

机构信息

Department of Electronics-Computer Education, Süleyman Demirel University, Isparta, Turkey.

出版信息

J Med Syst. 2011 Dec;35(6):1503-11. doi: 10.1007/s10916-009-9427-x. Epub 2010 Feb 2.

Abstract

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.

摘要

本工作使用数据挖掘来确定乳腺癌的治疗方法。为此,开发了软件来帮助肿瘤医生为乳腺癌患者建议应用治疗方法。使用来自安卡拉肿瘤医院的 462 名乳腺癌患者的数据来确定新患者的治疗方法。这个数据集是用 Weka 数据挖掘工具进行处理的。对这个数据集逐一应用分类算法,并比较结果以找到合适的治疗方法。开发的软件程序称为“治疗助手”,使用不同的算法(IB1、多层感知器和决策表)来找出每个属性给出更好结果的算法,以便预测,并使用 Java Net beans 界面。使用这个开发的软件工具为乳腺癌患者的手术后确定治疗方法。在数据挖掘过程的建模步骤中,为输出属性使用不同的 Weka 算法。对于激素治疗输出 IB1,对于他莫昔芬和放射治疗输出多层感知器,对于化学治疗输出决策表算法,与其他算法相比,显示出最佳的准确性性能。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,特别是在治疗决策步骤。数据挖掘可以帮助医生在短时间内做出决策。

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