The Process and Strategy Study of Business Communication

Lu, Yi Qing; Sun, Menghong

doi:10.2991/icemc-16.2016.203

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These methods assume that duplicate activities in a process trace are equivalent. Based on our analysis of trauma resuscitation workflow and previous work, each occurrence of an activity may have different underlying “intentions” [1][4][6]. For instance, over the course of a single trauma resuscitation, the trauma team may check the patient’s eyes at two different points in time for different reasons.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Medical Workflow Modeling Using Alignment-Guided State-Splitting HMM

Yang

Zhou

Chen

et al. 2017

2017 IEEE International Conference on Healthcare Informatics (ICHI)

View full text Add to dashboard Cite

Process mining techniques have been used to discover and analyze workflows in various fields, ranging from business management to healthcare. Much of this research, however, has overlooked the potential of hidden Markov models (HMMs) for workflow discovery. We present a novel alignment-guided state-splitting HMM inference algorithm (AGSS) for discovering workflow models based on observed traces of process executions. We compared the AGSS to existing methods using four real-world medical workflow datasets and a more detailed case study on one of them. Our numerical results show that AGSS not only generates more accurate workflow models, but also better represents the underlying process. In addition, with trace alignment to guide state splitting, AGSS is significantly more efficient (by a factor of O(n)) than previous HMM inference algorithms. Our case study results show that our approach produces a more readable and accurate workflow model that existing algorithms. Comparing the discovered model to the hand-made expert model of the same process, we found three discrepancies. These three discrepancies were reconsidered by medical experts and used for enhancing the expert model.

show abstract

Section: Introductionmentioning

confidence: 99%

“…To our knowledge, no existing workflow mining algorithm can properly model such duplicate activities. Recent work has presented a strategy to refine duplicate activity labels, but only during preprocessing [6]. We address this problem by modeling duplicate activities as different hidden states in an HMM.…”

Section: Introductionmentioning

confidence: 99%