基于Apriori算法的数据挖掘在移动医疗系统中的应用

针对医疗行业海量数据的数据挖掘应用少、基础差,数据分析的需求迫切等问题,提出一套创新型数据采集与挖掘方案.该方案选用Apriori算法就目前产科数据集展开关联分析,重点研究剖宫产与体征、药品之间的关联,并分析了产妇入院时间及新生儿出生时间分布与数量的关系.另外,还对关系到数据采集与传输效率的移动医疗系统进行研究,选用便携数字终端(portable digtital assistant,PDA)进行移动式数据采集,并阐述了基于新型分布式多层系统模型和SSH2框架的设计方案.在北京市某妇产医院的临床应用表明:该系统能够为医护人员提供精确、客观的数据支持,优化医护流程.数据挖掘分析结果对于药房的备药、发药,手术室准备,医护人员排班等具有指导意义和参考价值,可为后续医疗数据的统计和处理提供良好的技术基础.

Application of Data Mining in Mobile Health System Based on Apriori Algorithm

An innovative data collection and data mining scheme was proposed according to the urge demand for data analysis and poor application in data mining. Firstly, obstetric data was analyzed by using Apriori algorithm, mainly among caesarean delivery, vital signs and drugs. Then the admission time of pregnant women and birth time of newborns were analyzed. Finally, the mobile health system related to data collection and transmission efficiency was discussed by using PDA ( portable digital assistant) for portable data acquisition. And the distributed multi-layer system model and SSH2 framework were described. It shows that this system can provide accurate data and optimize medical process via clinical application in a Beijing maternity hospital. The analysis results are proved significant and valuable for medicine preparation and dispensing in pharmacy, operating room preparation, and staff scheduling. The performance of the scheme is proved effectiveness by the system deployed in hospital, which provides technical reference for future statistics and processing of medical data.