Process mining, an emerging data analytics method, has been used effectively in various
healthcare contexts including oncology, the study of cancer. Cancer is a complex disease …

The execution of processes leaves trails of event data in information systems. These event
data are analyzed to generate insights and improvements for the underlying process …

Event sequence data is increasingly available in various application domains, such as
business process management, software engineering, or medical pathways. Processes in …

Recent research has introduced ideas from concept drift into process mining to enable the
analysis of changes in business processes over time. This stream of research, however, has …

Rapidly changing business environments expose companies to high levels of uncertainty.
This uncertainty manifests itself in significant changes that tend to occur over the lifetime of a …

Modern business processes are embedded in a complex environment and, thus, subjected
to continuous changes. While current approaches focus on the control flow only, additional …

Work in organisations is often structured into business processes, implemented using
process-aware information systems (PAISs). These systems aim to enforce employees to …

Process mining provides techniques to learn models from event data. These models can be
descriptive (eg, Petri nets) or predictive (eg, neural networks). The learned models offer …

Process mining can help organizations by extracting knowledge from event logs. However,
process mining techniques often assume business processes are stationary, while actual …

Process mining focuses on applying data mining techniques over business process data.
Recently, with the improvements in sensoring, collection, and storage of event data, a big …