University of Twente Student Theses
Leveraging Machine Learning and Process Mining to Treat Anaemia with the Help of Prescription Records
Satici, Arda (2023) Leveraging Machine Learning and Process Mining to Treat Anaemia with the Help of Prescription Records.
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| Abstract: | According to WHO statistics, the global anaemia prevalence is around 30%, making anaemia one of the most encountered diseases. Hence, I wanted to focus on the effect of machine learning and process mining on the treatment studies of this common disease in my research paper. This research paper has the aim of working on the extension of a project that Mike Pingel has done before and to compare my findings with the findings of his project and share the results with the reader. The limitation of this research paper is that the methodology of this research paper should be kept the same as the project that I accepted as the foundation. That is, I can use the techniques used in that project in exactly the same way and should not make additional variants myself. In a branch such as machine learning where new developments are experienced every day, it would be a future improvement for my research if this project is repeated in the future with new machine learning algorithms and more recent MIMIC datasets and my deficiencies in this research paper are determined accordingly. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/96184 |
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