Obstacles and Misunderstandings Facing Medical Data Mining
Obstacles and Misunderstandings Facing Medical Data Mining
复制标题
医疗数据挖掘面临的障碍和误解
DOI：
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复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
A. Sami
中科院分区：
文献类型：
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作者：
A. Sami
医疗数据挖掘是数据挖掘领域中一个非常活跃和具有挑战性的研究领域。然而，从事医疗数据挖掘的研究人员应该意识到，在核心临床、牙科和护理领域，数据挖掘并不像我们想象的那样受欢迎，基于数据挖掘算法在这些期刊上发表结果并不容易。在这篇论文中，除了介绍我们在泌尿学中一个“成功的”KDD项目之外，我们还基于PubMed上的设计搜索和基于这些搜索的综述文献来支持我们的信念。我们的研究结果表明，很少有数据挖掘算法进入核心临床期刊。本文的结论是我们通过自己的经验收集到的原因。
Medical Data Mining is a very active and challenging research area in Data Mining community. However researchers entering Medical Data Mining should be aware that in core clinical, dentistry and nursing, data mining is not welcomed as much as we believe and publication of results in these journals based on Data Mining algorithms is not easily possible. In this paper, in addition to presenting one of our “successful” KDD projects in Urology that did not get to anywhere, we back up our belief based on designed searches on PubMed and review literature based on these searches. Our findings suggest that few Data Mining algorithms made their ways into core clinical journals. The paper concludes by reasons we have collected through our experiences.
粗糙集：多因素医疗结果的知识发现技术。
DOI：
10.1097/00002060-200001000-00022
发表时间：
2000
影响因子：
3
作者：
Ohrn,A;Rowland,T
通讯作者：
Rowland,T