A Fuzzy Non-linear Similarity Measure for Case-Based Reasoning Systems for Radiotherapy Treatment Planning

Abstract : This paper presents a decision support system for treatment planning in brain cancer radiotherapy. The aim of a radiotherapy treatment plan is to apply radiation in a way that destroys tumour cells but minimizes the damage to healthy tissue and organs at risk. Treatment planning for brain cancer patients is a complex decision-making process that relies heavily on the subjective experience and expert domain knowledge of clinicians. We propose to capture this experience by using case-based reasoning. Central to the working of our case-based reasoning system is a novel similarity measure that takes into account the non-linear effect of the individual case attributes on the similarity measure. The similarity measure employs fuzzy sets. Experiments, which were carried out to evaluate the similarity measure using real brain cancer patient cases show promising results.
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Harris Papadopoulos; Andreas S. Andreou; Max Bramer. 6th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations (AIAI), Oct 2010, Larnaca, Cyprus. Springer, IFIP Advances in Information and Communication Technology, AICT-339, pp.112-119, 2010, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-16239-8_17〉
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Rupa Jagannathan, Sanja Petrovic, Angela Mckenna, Louise Newton. A Fuzzy Non-linear Similarity Measure for Case-Based Reasoning Systems for Radiotherapy Treatment Planning. Harris Papadopoulos; Andreas S. Andreou; Max Bramer. 6th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations (AIAI), Oct 2010, Larnaca, Cyprus. Springer, IFIP Advances in Information and Communication Technology, AICT-339, pp.112-119, 2010, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-16239-8_17〉. 〈hal-01060658〉

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