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Medical decision making is a complex task in which many factors need to be taken into account. The project aims at developing a process-driven medical decision support system that effectively assists the treatment of cardiac patients. The system to be developed combines the results and methods of medicine, information technology, and process engineering in a unique way. The intelligent recommender system provides an objective picture of the activities of the cure and helps to guarantee the optimum decisions.

The decision support system to be developed helps the physician's work in order to make decisions for the patient the most appropriate (eg. choice of therapy). For this purpose, the system’s recommendations are based on the recommendations of ESC Guideline and information arising from the healthcare medical system. The integrated decision support processes provide medical support to such patient treatment processes that include complex decision-making situations, and in which the treatment process support can effectively increase the quality of the treatment flow.

The University participates in the elaboration of the following sub-tasks:

  • Modeling of Processes of Cardiac Patients’ Treatments: The task of the working group is to map medical expertise into process models and to integrate healthcare information data into the process models to support the decision making. Members of the workgroup work also on the development of a process modeling software that effectively helps to describe and model healthcare processes in BPMN.
  • Medical Treatment Process Scheduling: The aim of the sub-task is to develop an optimized treatment scheduling method that utilizes the parameters of treatment related to patient care to give a personalized optimum treatment schedule.
  • Analysis of Cardiological Treatment Processes: The aim of the sub-task is to develop process and data mining methods that enable monitoring of patients' treatment processes, characterization of treatments with quality indicators (KPI), and identifying bottlenecks of the treatment processes. Furthermore, the task of the working group is to develop a similarity-based recommender system and to process the free-text medical texts to support decision-making processes.


Consortium partner: Asseco Hungary