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

The association between allergic rhinitis and bronchial asthma, that is, whether it is a seqential process or independent diseases, has not been established. We confirmed that a 25 year-old woman with allergic rhinitis sensitized to Artemisia spp. pollens and house dust mites developed bronchial asthma during a 2 year follow-up period. Severe broncho-constriction was noted after inhalation of methacholine, and the bronchoprovocation test with extract of Korean Artemisia spp. pollen showed early bronchoconstiction. Total IgE and specific IgE antibodies to Artemisia absinthium increased, compared to the initial levels. It is suggested that some patients with allergic rhinitis progress to bronchial ashtma.
Adult ; Angiosperms ; Asthma/diagnosis/*etiology ; Bronchial Provocation Tests ; Case Report ; Female ; Hay Fever/*complications/diagnosis ; Human ; Korea ; *Pollen ; Skin Tests