摘要
随着电子病历全面普及,门诊和住院的检查、诊断、治疗等医疗数据的急剧增加,通过数据挖掘技术能够从这些数据中发现有价值的知识和规律,而关联规则挖掘是数据挖掘领域中的一个重要研究领域。论文以上海长征医院实际病历构建模型实验数据,采用Apriori关联规则挖掘算法,通过数据化的实验结论,验证强直性脊柱炎诊断中的一些经验知识,同时挖掘出数据中潜在的有效关联规则,这些关联规则对病情的诊断和治疗具有重要参考价值。
With the comprehensive popularization of electronic medical records and the sharp increase of medical data such as outpatient and inpatient examination,diagnosis and treatment,valuable knowledge and rules can be found from these data through data mining technology,and association rule mining is an important research field in the field of data mining.This paper constructs model experimental data based on the actual medical records of Shanghai Long March Hospital,uses the Apriori association rule mining algorithm,and verifies some empirical knowledge in the diagnosis of ankylosing spondylitis through the data-driven experimental conclusions.At the same time,the potential effective association rules in the data are mined,which have important refer-ence value for the diagnosis and treatment of disease conditions.
作者
盛小宝
吴歆
SHENG Xiaobao;WU Xin(Third Research Institute of the Ministry of Public Security,Shanghai 200030;Shanghai Changzheng Hospital,Shanghai 200010)
出处
《计算机与数字工程》
2025年第8期2108-2111,2132,共5页
Computer & Digital Engineering
基金
国家自然科学基金项目“基于AI的脊柱关节病早期诊断及疗效评估体系的建立”(编号:82271852)资助。
关键词
关联规则挖掘
强直性脊柱炎
智能诊断
人工智能
风湿免疫学
association rules mining
ankylosing spondylitis
intelligent diagnosis
artificial intelligence
rheumatism abnormalitie
