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JOURNAL

Cancer Informatics

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On the Significance of Fuzzification of the N and M in Cancer Staging

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Publication Date: 24 Jul 2014

Type: Methodology

Journal: Cancer Informatics

Citation: Cancer Informatics 2014:13 85-91

doi: 10.4137/CIN.S13765

Abstract

The tumor, node, metastasis (TNM) staging system has been regarded as one of the most widely used staging systems for solid cancer. The “T” is assigned a value according to the primary tumor size, whereas the “N” and “M” are dependent on the number of regional lymph nodes and the presence of distant metastasis, respectively. The current TNM model classifies stages into five crisp classes. This is unrealistic since the drastic modification in treatment that is based on a change in one class may be based on a slight shift around the class boundary. Moreover, the system considers any tumor that has distant metastasis as stage 4, disregarding the metastatic lesion concentration and size. We had handled the problem of T staging in previous studies using fuzzy logic. In this study, we focus on the fuzzification of N and M staging for more accurate and realistic modeling which may, in turn, lead to better treatment and medical decisions.


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What Your Colleagues Say About Cancer Informatics
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Compared with other journals we considered for publishing, Cancer Informatics provided extremely rapid but quality turnaround from draft submission to a flawlessly typeset final publication.  Moreover, sharing the article is now as easy as sharing a link with no subscriptions required, and additional code and data files are equally accessible, supporting reproducible research.  Because it has published many of our references we feel confident that our target readership must follow the journal.  This is further ...
Dr Seppo Karrila (Prince of Songkla University, Thailand)
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