Abstract: ObjectiveTo establish an auxiliary diagnosis system of infectious disease and to improve the accuracy, time liness in the diagnosis of infectious disease.MethodsThe data on 343 kinds of infectious disease symptoms,signs were collected and Baye sian classification model was constructed.ResultsThe correct identification of infectious diseases was ranked first, with about 60% of the averaged iagnostic accuracy,and the accuracy was 92.7% in the practical application of H1N1 in fluenza outbreak.ConclusionThe system enables a more rational and accurate diagnosis of infectious disease through reducing misdiagnosis and improving the accuracy of diagnosis of infectious disease.