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Medical Treatment Process Modeling Based on Process Mining and Treatment Patterns

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摘要 activities.Ex-periments on a synthetic log of the non-secondary hy-pertension MTP and empirical findings demonstrate the effectiveness of our approach.The results show that the process mining in our approach framework can automatically generate more accurate MTP mod-els,and the subprocess models based on treatment pat-terns make the models easy to understand.
作者 Liqin Yang Guosheng Kang Liang Zhang
机构地区 School of Computer Science Shanghai Key Laboratory of Data Science Institute of Intelligent Electronics and Systems Computer Teaching and Research Section School of Computer Science and Engineering
出处 《China Communications》 SCIE CSCD 2021年第12期332-349,共18页 中国通信（英文版）
基金 Chinese National Key Research and Development Program(No.2017YFB1400604).
关键词 business process modeling medical treat-ment processes treatment patterns clinical practice guidelines
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论] R197 [医药卫生—卫生事业管理]
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  • 1Van der Aalst WMP. Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer-Verlag, 201 1.
  • 2Van der Aalst WMP, De Medeiros AKA, Weijters AJMM. Genetic process mining. In: Proc. of the Applications and Theory of Petri Nets 2005. LNCS 3536, Springer-Verlag, 2005.48-69.
  • 3Van der Aalst W, Weijters T, Maruster L. Workflow mining: Discovering process models from event logs. IEEE Trans. on Knowledge and Data Engineering, 2004,16(9): 1128-1142. [doi: 10.1109/TKDE.2004.47].
  • 4Wen LJ, Wang JM, Sun JG. Detecting implicit dependencies between tasks from event logs. In: Proc. of the Frontiers of WWW Research and Development-APWeb 2006. Springer-Verlag, 2006.591-603. [doi: 10.1007/11610113_52].
  • 5Weijters AJMM, Ribeiro JTS. Flexible heuristics miner (FHM). In: Proc. of the IEEE Syrup. on Computational Intelligence and Data Mining (CIDM). IEEE, 2011.310-317. [doi: 10.1109/CIDM.2011.5949453].
  • 6Weijters AJMM, van der Aalst WMP. Rediscovering workflow models from event-based data using little thumb. Integrated Computer Aided Engineering, 2003,10(2): 151-162.
  • 7Van Dongen BF, Van der Aalst WMP. Multi-Phase process mining: Aggregating instance graphs into EPCs and Petri nets. In: Proc. of the 2nd Int'l Workshop on Applications of Petri Nets to Coordination, Workflow and Business Process Management (PNCWB). Citeseer, 2005.
  • 8Van Dongen BF, Van der Aalst WMP. Multi-Phase process mining: Building instance graphs. In: Proc. of the Conceptual Modeling-ER 2004. Springer-Verlag, 2004. 362-376. [doi: 10. 1007/978-3.540-30464-729].
  • 9De Medeiros AKA, Weijters AJMM, Van der Aalst WMP. Genetic process mining: an experimental evaluation. Data Mining and Knowledge Discovery, 2007,14(2):245-304. [doi: 10.1007/s10618-006-0061-7].
  • 10De Medeiros AKA, Weijters AJMM, Van der Aalst WMP. Genetic process mining: A basic approach and its challenges. In: Proc. of the Business Process Management Workshops. Springer-Verlag, 2006. 203-215. [doi: 10.1007/11678564 18].

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China Communications
2021年 第12期

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