University of Twente Student Theses
Evaluating the effectiveness of a reinforcement learning model in customizing colonoscopy screening policies
Blik, Daniël (2024) Evaluating the effectiveness of a reinforcement learning model in customizing colonoscopy screening policies.
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| Abstract: | Colorectal and rectum cancer (CRC) is a major global health concern, contributing to both morbidity and mortality rates and decreasing the quality of life of patients. This cancer originates from small growths also referred to as polyps. These polyps if not detected and removed promptly can grow into tumors. To detect these polyps a procedure called colonoscopy is used. This procedure allows for the visual examination of the colon's interior and the removal of polyps. The colonoscopy procedure is one of the most effective procedures for the detection and removal of polyps. However, the optimal timing policies for colonoscopy procedures remain a topic of debate. This thesis aims to contribute to the ongoing discussion on colonoscopy screening guidelines. This paper will evaluate existing screening guidelines and existing reinforcement learning models by literature review. After which it will evaluate the performance of a new model based on partial observability utilizing a simulation. This model takes into account more personalised aspects of the policy recommendation. Finally, the paper attempts to make a valuable conclusion which may contribute to the ongoing debate on colonoscopy screening guidelines. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 44 medicine, 54 computer science |
| Programme: | Business & IT BSc (56066) |
| Link to this item: | https://purl.utwente.nl/essays/101167 |
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