Process model comprehension is essential for a variety of technical and managerial tasks.
To facilitate comprehension, process models are often divided into subprocesses when they …

Background Knowledge of post-myocardial infarction (MI) disease risk to date is limited—yet
the number of survivors of MI has increased dramatically in recent decades. We investigated …

Process mining has significantly transformed business process management by introducing
innovative data-based analysis techniques and empowering organizations to unveil hidden …

Large Language Models (LLMs) are likely to play a prominent role in future AI-augmented
business process management systems (ABPMSs) catering functionalities across all system …

Over the past few years, several software companies have emerged that offer process
mining tools to assist enterprises in gaining insights into their process executions. However …

Machine learning models are routinely integrated into process mining pipelines to carry out
tasks like data transformation, noise reduction, anomaly detection, classification, and …

Abstract Predictive Process Monitoring (PPM) extends classical process mining techniques
by providing predictive models that can be applied at runtime during the execution of a …

Abstract Finite variant of Linear Temporal Logic (LTL f) is increasingly popular in Artificial
Intelligence (AI). Indeed, several AI applications rely on checking the satisfiability of temporal …

Many real-life processes naturally define partial orders over the activities they are composed
of. Partial orders can be used as a graph-like representation of process behavior, allowing …

Process mining has become a cornerstone of process analysis and improvement over the
last few years. With the widespread adoption of process mining tools and libraries, the …