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A cloud-based fuzzy expert system for the risk assessment of chronic kidney diseases

Listed author(s):
  • Chien-Hua Wu
  • Ruey-Kei Chiu
  • Shin-An Wang
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    This paper aims to construct a cloud-based fuzzy expert system for the risk assessment of chronic kidney disease (CKD). The neural networks are firstly modelled for the detection of early chronic kidney disease while fuzzy rule-based expert system is employed for risk assessment. Firstly, three different neural network models are developed and experimented followed by the effectiveness measurement of three models based on the criteria of accuracy, sensitivity, and specificity among them. Secondly, the fuzzy rule-based expert system is developed and then is deployed to the cloud platform for conducting the self-risk assessment by the public users. In the ultimate goal, we anticipate that the expert system may also support CKD physicians an alternative to more accurately detect and assess the chronic kidney disease in its early stage of a patient. An online usefulness survey was also conducted. The result shows that there are 88.4% of all users responding to 'Helpful' based on our five-scale metrics. It was concluded that the system is helpful for a user to conduct a self-assessment on risk of kidney health status.

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    Article provided by Inderscience Enterprises Ltd in its journal Int. J. of Business and Systems Research.

    Volume (Year): 9 (2015)
    Issue (Month): 4 ()
    Pages: 315-333

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    Handle: RePEc:ids:ijbsre:v:9:y:2015:i:4:p:315-333
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