基于统计α算法的临床路径过程挖掘

发布时间：2018-02-28 02:16

  本文关键词： 临床路径 过程挖掘 重名活动 活动关系 统计α算法　出处：《浙江大学学报(工学版)》2017年10期 　论文类型：期刊论文

【摘要】：针对临床路径事件日志中存在的重名活动和噪音数据,提出集成重名活动判别的过程挖掘算法:统计α算法.给出一套完整的重名活动的判别规则,用于识别过程挖掘中的重名活动并进行相应预处理,有效地提高了过程挖掘的准确性;提出基于经典α算法改进的统计α算法,用于消除事件日志中各种噪音的影响.该算法在临床路径数据量较大的情形下,保证了结果准确率和运算效率.统计α算法在三甲医院的临床数据上得到成功应用,与经典α算法和遗传算法相比,该算法在效率和准确性上更具优越性.
[Abstract]:In view of the data of duplicate name activity and noise in clinical path event log, a process mining algorithm of integrating duplicate name activity discrimination is proposed: statistical 伪 algorithm, and a set of complete discriminant rules for duplicate name activity are given. It can be used to identify and preprocess the duplicate name activities in process mining, which can effectively improve the accuracy of process mining, and bring forward an improved statistical 伪 algorithm based on classical 伪 algorithm. It is used to eliminate the influence of various noises in the event log. The algorithm ensures the accuracy and efficiency of the results under the condition of large amount of data of the clinical path. The statistical 伪 algorithm has been successfully applied in the clinical data of the third Class A Hospital. Compared with classical 伪 algorithm and genetic algorithm, this algorithm is more efficient and accurate.
【作者单位】： 同济大学机械与能源工程学院;
【基金】：国家自然科学基金资助项目(51375290) 上海航天科技创新基金资助项目(SAST2015054) 中央高校基本科研业务费人才资助项目
【分类号】：O213;R197.3
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本文编号：1545326