A cost-effective, case-control study on the association between breast cancer and pregnancy through web mining.

Hong-Jun Yoon, Songhua Xu, Georgia Tourassi
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引用次数: 1

Abstract

We report a case-control, breast cancer epidemiological study through mining people stories from the Internet. The aim of the study is to test whether mining openly available, personal stories from the Internet can be a cost-effective way for reliable epidemiological discoveries. As a case study, we focus on the association between breast cancer risk and pregnancy, which is clearly established through controlled clinical survey studies. Specifically, we mined 30,000 online obituary articles. Replicating a case-control study design, our web mining based approach confirmed the general trends reported by traditional epidemiological studies. Our web mining study demonstrates promising preliminary evidence that online content mining can be a cost-effective way for epidemiological knowledge discovery.

通过网络挖掘对乳腺癌和怀孕之间关系的一项具有成本效益的病例对照研究。
我们报告了一项病例对照的乳腺癌流行病学研究,通过从互联网上挖掘人们的故事。这项研究的目的是测试从互联网上公开获取的个人故事是否可以成为一种经济有效的方法,以获得可靠的流行病学发现。作为一个案例研究,我们关注乳腺癌风险与怀孕之间的关系,这是通过对照临床调查研究明确建立的。具体来说,我们挖掘了3万篇在线讣告文章。复制病例对照研究设计,我们基于网络挖掘的方法证实了传统流行病学研究报告的一般趋势。我们的网络挖掘研究展示了有希望的初步证据,即在线内容挖掘可以是一种具有成本效益的流行病学知识发现方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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