Clinical guidelines aim at improving the quality of care processes based on evidence-based insights. However, there may be good reasons to deviate from such guidelines or the guidelines may provide insufficient support as they are not tailored towards a particular setting (e.g., hospital policy or patient group characteristics). Therefore, we propose an approach to mediate between event data re...

Process mining is prominent contemporary research topic. This paper describes requirements to be fulfilled for effective practical adoption on the basis of application scenarios and a sample project.

To be able to provide safe, effective, and efficient care in today’s competitive environment, hospitals must have process visibility and continuously improve quality (Kemafor, Sheth, Cardoso, Miller, & Kochut, 2003). Process visibility refers to the ability to see and understand all aspects of a process at any point in time (Klotz, Horman, Bi, & Bechtel, 2008). However, the complex nature and t...

This paper describes the results of the exploratory process mining efforts on the incident management process event log provided by Volvo IT Belgium. Specific areas of interest provided by the process owner are analyzed as well as some additional areas of interest that qualified for further investigation based on the information provided. Interesting results include uncovering specific support ...

Background and Objectives: Arteriovenous fistula is a popular vascular access method for surgical treatment of hemodialysis patients. The method, however, is associated with a high rate of early failure varying in the range of 20-60%. Predicting early Arteriovenous fistula failure and its risk factors can help reduce its incidence, its hospitalization rate, and associated costs. In this study, ...

Decision support systems (DSSs) are prevalent information systems for decision making in many competitive business environments. In a DSS, decision making process is intimately related to some factors which determine the quality of information systems and their related products. Traditional approaches to data analysis usually cannot be implemented in sophisticated Companies, where managers ne...

Process mining involves discovering, monitoring, and improving real processes by extracting knowledge from event logs in information systems. has become an important topic recent years, as evidenced a growing number of case studies commercial tools. Current this area assume that records are created separately conceptual model (CM). Techniques then used to discover missing conformance with the C...

Process mining is a research discipline that applies data analysis and computational intelligence techniques to extract knowledge from event logs of information systems. It aims provide new means discover, monitor, improve processes. has gained particular attention over recent years process software tools, both academic commercial, have been developed. This paper provides survey tools. identifi...

Free-choice nets, a subclass of Petri have been studied for decades. They are interesting because they many desirable properties normal nets do not and can be analyzed efficiently. Although the majority process models used in practice inherently free-choice, most users (even modeling experts) aware free-choice net theory associated analysis techniques. This paper discusses context mining busine...