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A Hybrid Intelligent System for the Disease Risk Evaluation

Author

Listed:
  • Sheng Jen Jian

    (Fu Jen Catholic University, Taiwan)

  • Kang-Hong Liou

    (Fu Jen Catholic University, Taiwan)

  • Ruey Kei Chiu

    (Fu Jen Catholic University, Taiwan)

Abstract

This paper attempts to develop a hybrid intelligent system for the risk evaluation of coronary heart disease by leveraging the artificial intelligent techniques of combining artificial neural network and fuzzy expert system. The statistical analytical method and the multilayer perceptron of neural network are taken respectively to identify the significant causing factors for the coronary heart disease. The factors are then applied for developing the fuzzy expert system of risk evaluation. Furthermore, the system is deployed to the cloud for being used by the publics. The result of cloud deployment is also evaluated in terms of advantages, and disadvantages. The accuracy rate of this system from case evaluation may reach to 80 percent. Although this figure is acceptable from the viewpoints of experts but it may be improved in order to be used with more reliable in practice. Additionally, the cost, performance, and data security are also concerned and need to be further evaluated in the subsequent study of this paper.

Suggested Citation

  • Sheng Jen Jian & Kang-Hong Liou & Ruey Kei Chiu, 2014. "A Hybrid Intelligent System for the Disease Risk Evaluation," Human Capital without Borders: Knowledge and Learning for Quality of Life; Proceedings of the Management, Knowledge and Learning International Conference 2014,, ToKnowPress.
    • Handle: RePEc:tkp:mklp14:837-844
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