关联规则在小儿肺炎病案信息挖掘中的应用

目的：探讨关联规则在小儿肺炎病案信息挖掘中的应用。方法：以小儿肺炎的病案信息为切入点，合并诊疗数据，摘录用药信息并组建数据库，对药物进行频次统计分析，建立Apriori模型，进行关联规则分析。结果：共获得小儿肺炎诊断记录584条，使用频次超过100次的药物有20种，共获得联合用药关联规则60则。抗炎、祛痰、平喘、止咳、抗感染是肺炎患儿的主要治疗措施。结论：治疗小儿肺炎时最常使用的药物符合小儿肺炎治疗的用药特点，与小儿肺炎治疗的临床指南相符，从而验证了关联规则分析在病案信息挖掘中的有效性。

Application of association rules in mining medical records of children pneumonia

Objective To study the application of association rules in mining information in medical records of children pneumonia.Methods A database was developed, which covers the information in medical records of children pneumonia, medical diagnosis and treatment data, and drug use information, and an Apriori model was established by statistical analysis of drug use frequencies for analyzing the association rules in mining information in medical records of children pneumonia. Results A total of 584 diagnostic records of children pneumonia were mined from the database, 20 drugs were used more than 100 times, and 60 association rules were discovered for drugs used in combination. Anti-inflammation, phlegm removing, asthma and cough relieving, and anti-infection were the main therapies for children pneumonia. Conclusion The drugs commonly used in treatment of children pneumonia are in line with the drug use characteristics and in agreement with the clinical guidelines on the treatment of children pneumonia, which has thus verified the effectiveness of association rules in mining information in medical records.