Yonsei Med J.  1992 Mar;33(1):72-80. 10.3349/ymj.1992.33.1.72.

The development of a decision support system for diagnosing nasal allergy

Affiliations
  • 1Department of Preventive Medicine and Public Health, Yonsei University College of Medicine, Seoul, Korea.
  • 2Department of Otolaryngology, Inha University of College, Korea.
  • 3Department of Otolaryngology, Yonsei University College of Medicine, Korea.
  • 4Department of Otolaryngology, inje University, Korea.
  • 5Department of Otolaryngology, Paik Hospital, Korea.
  • 6Department of Electronic Engineering, Yonsei University College of Engineering, Korea.

Abstract

This paper deals with the problem of improving the capability of the medical decision support system (MDSS) for diagnosing nasal allergy by integrating the previously developed expert system with the neural network approach. Three knowledge acquisition methods were used to develop the expert system: statistical, rule-based, and the combined approach. Among the three, a combined approach showed the best prediction rate based on discriminant analysis. Using the results of a combined approach as input values, the neural network was developed using back-propagation method. Unlike the expert system, the neural network system provides the resulting allergy status in probabilistic terms. Managerial as well as legal issues were also discussed in this paper.

Keyword

Expert system; artificial intelligent; neural network; nasal allergy; MDSS

MeSH Terms

*Decision Support Techniques
Hay Fever/*diagnosis
Human
Rhinitis, Allergic, Perennial/*diagnosis
Support, Non-U.S. Gov't
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