Statistical α-algorithm based process mining on clinical pathway

被引：0

作者：

Yu J.-B. ^{[1
]}

Dong C.-Y. ^{[1
]}

Li C.-F. ^{[1
]}

Liu H.-Q. ^{[1
]}

机构：

[1] School of Mechanical Engineering, Tongji University, Shanghai

来源：

Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2017年 / 51卷 / 10期

关键词：

Activity relationship; Clinical pathway; Cognominal activity; Process mining; Statistical; α-algorithm;

D O I：

10.3785/j.issn.1008-973X.2017.10.001

中图分类号：

学科分类号：

摘要：

A process mining algorithm integrated with cognominal activities identification rules (called statistical α-algorithm) was proposed for dealing with the cognominal activities and noise in clinical pathway event logs. A set of cognominal activities identification rules was proposed for the pretreatment of process mining to identify and dispose the cognominal activities in the event logs, which improved the accuracy of the proposed method. The statistical α-algorithm was developed based on the classicalα-algorithm to eliminate the influence of process noise in event logs. The proposed method showed high accuracy and efficiency when there were large amounts of clinical data. Statistical α-algorithm was successfully applied to the real-world clinical data from a hospital. The experimental results indicated that the algorithm was superior in efficiency and accuracy compared with the classical α-algorithm and the genetic algorithm. © 2017, Zhejiang University Press. All right reserved.

引用

页码：1881 / 1890

页数：9

共 19 条

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