传染病辅助判别系统建立及应用效果评价

Auxiliary diagnosis system of infectious diseases and its application

目的通过建立传染病辅助判别系统,避免传统的经验判断与个人的主观因素影响而带来的决策失误,提高传染病疫情现场判别的准确性、时效性及科学性。方法收集343种传染病症状、体征数据,运用贝叶斯算法建立分类模型。结果应用该系统对多起传染病疫情进行分析,判别排在第1位的传染病均与实际相符,其平均的诊断精度约为60%,在甲型H1N1流感疫情的实际应用中精度为92.7%。结论该系统降低了疫情处置工作中的漏诊、误诊率,增加了传染病疫情诊断的准确性。

Objective To establish an auxiliary diagnosis system of infectious disease and to improve the accuracy,timeliness in the diagnosis of infectious disease.Methods The data on 343 kinds of infectious disease symptoms,signs were collected and Bayesian classification model was constructed.Results The correct identification of infectious diseases was ranked first,with about 60% of the average diagnostic accuracy,and the accuracy was 92.7% in the practical application of H1N1 influenza outbreak.Conclusion The system enables a more rational and accurate diagnosis of infectious disease through reducing misdiagnosis and improving the accuracy of diagnosis of infectious disease.