Comparison of alternative knowledge model for the diagnosis of asthma

摘要

This paper compared three knowledge models (namely, neural network, case-based reasoning, and discriminant analysis) for the diagnosis of asthma. The data were collected from 294 patients with asthmatic symptoms who visited the Bronchial Asthma Clinics, Internal Medicine Department of Yonsei University Severance Hospital from June 1992 to May 1995. Diagnostic capabilities for the three knowledge models varied. The neural network had the best overall prediction rate (92%) and the best prediction rate for asthma (96%); the discriminant analysis had the best prediction rate for non-asthma (80%); and the CBR had the lowest prediction rates in all categories.