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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98680

    Title: Cluster-based Classification of Diabetic Nephropathy among Type 2
    Authors: Guan-Mau Huang;Yu-Chun Lee;Julia Tzu-Ya Weng;Yi-Cheng Chen;Lawrence Shih-Hsin Wu
    Contributors: 資訊工程學系暨研究所
    Keywords: type 2 diabetes
    diabetic nephropathy
    Date: 2014-05-07
    Issue Date: 2014-09-10 01:46:22 (UTC+8)
    Abstract: The prevalence of type 2 diabetes is increasing at an alarming rate. Various complications are associated with type 2 diabetes, with diabetic nephropathy being the leading cause of renal failure among diabetics. Often, when patients are diagnosed with diabetic nephropathy, their
    renal functions have already been significantly damaged, speeding up the progression towards end stage renal disease. Therefore, a risk prediction tool may be beneficial for the implementation of early treatment and prevention. In the present study, we propose to develop a prediction model integrating clustering and classification approaches for the
    identification of diabetic nephropathy among type 2 diabetes patients. Clinical and
    genotyping data are obtained from 345 type 2 diabetic patients(160 with non-diabetic
    nephropathy and 185 with diabetic nephropathy). The performance of using clinical features alone for cluster-based classification is compared with that of utilizing a combination of clinical and genetic attributes. We find that the inclusion of genetic features yield better
    prediction results. Further refinement of the proposed approach has the potential to facilitate the accurate identification of diabetic nephropathy and the development of better treatment in a clinical setting.
    Relation: The 3rd International Congress on Natural Sciences and Engineering (ICNSE'14), pp. 861-867.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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