The development of a decision support system for diagnosing nasal allergy.
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.
Chae
Y M
YM
Department of Preventive Medicine and Public Health, Yonsei University College of Medicine, Seoul, Korea.
Jang
T Y
TY
Park
I Y
IY
Chung
S K
SK
Park
M
M
D003661:Decision Support Techniques; D006801:Humans; D012221:Rhinitis, Allergic, Perennial / Q000175:diagnosis*; D006255:Rhinitis, Allergic, Seasonal / Q000175:diagnosis*