English  |  正體中文  |  简体中文  |  Items with full text/Total items : 63184/95884 (66%)
Visitors : 4524052      Online Users : 87
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/103099

    Title: Construction of a Prediction Model for Nephropathy among Obese Patients Using Genetic and Clinical Features
    Authors: Huang, Guan-Mau;Chen, Yi-Cheng;Weng, Julia Tzu-Ya
    Contributors: 淡江大學資訊工程學系
    Keywords: obesity;nephropathy prediction;personalized diagnostic support system
    Date: 2015-05-19
    Issue Date: 2015-05-18 19:25:50 (UTC+8)
    Publisher: Springner
    Abstract: Obesity is a complex disease arising from an excessive accumula-tion of body fat which leads to various complications such as diabetes, hyper-tension, and renal diseases. The growing prevalence of obesity is also becom-ing a major risk factor for nephropathy. When patients are diagnosed with nephropathy, their progression towards renal failure is usually inevitable. Therefore, a prediction tool will help medical doctors identify patients with a higher risk of developing nephropathy and implement early treatment or pre-vention. In this study, we attempted to construct a diagnostic support system for nephropathy using clinical and genetic traits. Our results show that pre-diction models involving the use of both genetic and clinical features yielded the best classification performance. Our finding is in accordance with the complex nature of obesity-related nephropathy and support the notion of us-ing genetic traits to design a personalized diagnostic model.
    Relation: The 2nd International Workshop on Pattern Mining and Application of Big Data (BigPMA 2015) (in conjunction with PAKDD 2015)
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

    Files in This Item:

    File Description SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback