Knowledge Extraction from Prostate Cancer Data

D. Delen, N. Patil
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引用次数: 22

Abstract

Although cancer research has generally been clinical and/or biological in nature, in recent years, data driven analytic research has become a common complement. In medical domains where data and analytics driven research is successfully applied, new and novel research directions are identified to further advance the clinical and biological studies. Specifically, it is the combination of the serious effects of cancer, the promising results of prior analytical research in related fields, the potential benefits of the expected research outcomes and the desire to further understand the nature of cancer that provided the motivation for this research effort. Therefore, the main objective of this research has been to take advantage of the available data mining tools and techniques to develop accurate prediction models for prostate cancer survivability, and to explain the prioritized importance of the prognostic factors.
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从前列腺癌数据中提取知识
虽然癌症研究通常是临床和/或生物学性质的,但近年来,数据驱动的分析研究已成为一种常见的补充。在成功应用数据和分析驱动研究的医学领域,确定了新的研究方向,以进一步推进临床和生物学研究。具体来说,正是癌症的严重影响、相关领域先前分析研究的有希望的结果、预期研究结果的潜在好处以及进一步了解癌症本质的愿望结合在一起,为这项研究工作提供了动力。因此,本研究的主要目的是利用现有的数据挖掘工具和技术来开发前列腺癌生存能力的准确预测模型,并解释预后因素的优先重要性。
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