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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 mining techniques have been applied to the visualization, interpretation, and analysis of medical processes. However, only a very limited amount of process data necessary for these analyses is publicly available, especially in the medical field because of patients' privacy. This limits novel medical process research to using insufficiently large or randomly-generated synthetic datasets. Our...
Trace alignment algorithms have been used in process mining for discovering the consensus treatment procedures and process deviations. Different alignment algorithms, however, may produce very different results. No widely-adopted method exists for evaluating the results of trace alignment. Existing reference-free evaluation methods cannot adequately and comprehensively assess the alignment quality...
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