In this paper, an application of fuzzy-based expert
system for respiratory infection diagnostic is introduced. Due to
the symptoms of respiratory infections, such as influenza and
common cold, are very similar. It’s very difficult to determine if
patients got influenza, common cold or other respiratory
infections in first stage of exacerbation. In this paper, several
fuzzy rules for diagnostic respiratory infection are made
according doctor’s experience. The knowledge is adopted and
extracted for building expert system. In experiments, 50 virtual
patients are generated with different symptoms for testing
performance of proposed system. The proposed method exhibits
higher accuracy for judging patients’ disease (respiratory
infection).