University of Twente Student Theses
Subpopulation process mining in health
Kalcheva, Y.K. (2023) Subpopulation process mining in health.
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| Abstract: | Process mining is a technique used for analyzing processes based on event logs. In this study, process mining techniques will be applied in the health care sector for evaluation of cancer and breast cancer subpopulations. Therefore, a publicly available online MIMIC-III dataset will be used for data extraction as it contains data from the intensive care units of a large hospital. In addition, this research is a continuation of previous studies on this topic and will be extended in terms of data quality and machine learning. For improving the quality of selected data for this research project, the methodology of CRISP-DM (CRoss Industry Standard Process for Data Mining) model is followed. Moreover, process mining techniques are applied on the extracted cancer- and breast cancer- related data which helped for finding inconsistencies in the datasets. In addition, the results showed that the combination of machine learning techniques can work together with process mining. However, the data need to be carefully selected so that the results can be applicable. This project can be elaborated in the future by using real-world databases. Furthermore, it can be extended by doing research on more machine learning methods which can be used with process mining techniques. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 58 process technology |
| Programme: | Creative Technology BSc (50447) |
| Link to this item: | https://purl.utwente.nl/essays/94649 |
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