基于过程挖掘的临床路径Petri网建模

Clinical Pathway Modeling by Petri Net Based on Process Mining

摘要:

提出基于统计α算法的临床路径Petri网模型，将Petri网和基于统计α算法的过程挖掘算法集成，从事件日志中挖掘重要信息，获得完善的诊疗流程，并在此基础上建立Petri网模型，有效实现诊疗流程的优化和改进.通过仿真数据试验，验证了本文提出的统计α算法相较于经典α算法在准确度和运行时间上有着较大的优势.并将模型运用到临床路径真实数据上，证明了模型的有效性和准确性.

Abstract:

This paper proposed a clinical pathway Petri net model based on statistical αalgorithm, which integrate the basic Petri net with process mining algorithm based on statistical αalgorithm. This model can obtain medical procedure from event log and build clinical pathway Petri net model on the procedure. The medical procedure could be optimized and improved by analysis of the Petri net model. Simulation results shows that the statistical αalgorithm performs better in accuracy and efficiency than classic αalgorithm. The proposed model is verified on the real data of clinical pathway.