Stomach and esophageal cancer are in the top ten most common cancers worldwide, both with high mortality rate. Approximately one-third of these patients have metastases at initial diagnosis and should receive personalized palliative care to improve their remaining life time. However, there is a lack of consensus about personalized palliative care options. This often leads to difficulties in determining the right treatment pathway for individual patients. This study investigates the application of process mining techniques on palliative care pathways for stomach and esophageal cancer to obtain an evidence-based understanding of which palliative treatments are commonly carried out in clinical practice and how they are associated with patients’ survival time. Given the high variability of the treatment pathways, ‘local models’ are derived, rather than end-to-end process models, which are then validated with the aid of physicians. In addition, this study also investigates the use of predictive process monitoring techniques to predict patients’ life expectancy. The results show the benefit of taking the process-flow into account in predicting the outcome of the palliative treatments.

In many business processes, knowledge workers collect information and make decisions about business entities. Artifact-centric process (ACP) models have been proposed to represent such knowledge-intensive processes. Declarative ACP models use precise business rules to define flexible process executions. However, in many business situations knowledge experts have to deal with uncertainty and vagueness. Currently, how to deal with such situations cannot be expressed in declarative ACP models. We propose to use the fuzzy logic framework to model uncertainty in such models. Using Guard-Stage-Milestone (GSM) schemas as declarative ACP notation, we show how GSM schemas can be adapted for modeling gradual progress of real-life knowledge-intensive processes via a fuzzy logic interface. We evaluate the proposed fuzzy GSM schemas in real-life scenarios of airport ground operations and healthcare services.