Abstract
Breast Cancer is the most common invasive cancer in women worldwide. Indeed, it is imperative to investigate which factors influence the development of this disease in order to improve the efficiency of the treatment and to allow for a balanced follow-up. In fact, this article has in mind an original Case Based Reasoning (CBR) approach to problem solving, complemented with a novel approach to Knowledge Representation and Reasoning that takes into consideration the data items entropic states. It works towards cancer’s assessment after Neoadjuvant Chemotherapy in terms of its size, shape, and texture.
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Acknowledgments
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.
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Neves, J. et al. (2019). Prediction of Neoadjuvant Chemotherapy Outcome in Breast Cancer Patients. In: Ntalianis, K., Vachtsevanos, G., Borne, P., Croitoru, A. (eds) Applied Physics, System Science and Computers III. APSAC 2018. Lecture Notes in Electrical Engineering, vol 574 . Springer, Cham. https://doi.org/10.1007/978-3-030-21507-1_45
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