A survey and analysis of Electronic Healthcare Record standards
ACM Computing Surveys (CSUR)
Machine Learning: An Algorithmic Perspective
Machine Learning: An Algorithmic Perspective
Using clinical preferences in argumentation about evidence from clinical trials
Proceedings of the 1st ACM International Health Informatics Symposium
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
BPM'06 Proceedings of the 4th international conference on Business Process Management
On enabling integrated process compliance with semantic constraints in process management systems
Information Systems Frontiers
Data transformation and semantic log purging for process mining
CAiSE'12 Proceedings of the 24th international conference on Advanced Information Systems Engineering
CAiSE'12 Proceedings of the 24th international conference on Advanced Information Systems Engineering
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The formalization and analysis of medical guidelines play an essential role in clinical practice nowadays. Due to their inexorably generic nature such guidelines leave room for different interpretation and implementation. Hence, it is desirable to understand this variability and its implications for patient treatment in practice. In this paper we propose an approach for comparing guideline-based treatment processes with empirical treatment processes. The methodology combines ideas from workflow modeling, process simulation, process mining, and statistical methods of evidence-based medicine. The applicability of the approach is illustrated based on the Cutaneous Melanoma use case.