Abstract
Breast cancer is the most common and mortal carcinosis in women and thus a major topic in clinical oncology. Treatment planning features a complex decision making about the various therapy concepts and their possible combinations. The physician plans treatment of a patient based on therapy guide lines and knowledge acquired in similar former patient cases. In particular the latter aspect requires the processing of large amounts of information in order to identify the medically relevant cases. This implies the urgent need for a decision support system in clinical routine. This work introduces a model for description of patient cases in terms of their crucial attributes and a mathematical function concept for the notion of medical relevance. These concepts are then used for an automated search on the set of former patient cases resulting in a comprehensive overview of the medically relevant ones with the therapy steps carried out therein and the observed outcomes. Provided with this information, the physician can conduct time-efficient planning of high quality breast cancer therapies for each individual patient case.
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Acknowledgments
This ongoing research&development project is financed by Roche Pharma AG. The authors would like to thank Prof. Dr. Hans Hagen from the Faculty of Computer Sciences of the Technical University of Kaiserslautern (Germany), for the supervision of [5].
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Scherrer, A., Rüdiger, P., Dinges, A., Küfer, KH., Schwidde, I., Kümmel, S. (2014). A Decision Support Concept for Advanced Treatment Planning for Breast Cancer. In: Huisman, D., Louwerse, I., Wagelmans, A. (eds) Operations Research Proceedings 2013. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-07001-8_55
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DOI: https://doi.org/10.1007/978-3-319-07001-8_55
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