Prediction of Neoadjuvant Chemotherapy Outcome in Breast Cancer Patients

• Autor(a) principal: Neves, José
• Data de Publicação: 2019
• Outros Autores: Dias, Almeida, Silva, Cristiana, Ferreira, Diana, Costa, Luís, Ferraz, Filipa, Alves, Victor, Neves, João, Ribeiro, Jorge, Vicente, Henrique
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10174/25882; https://doi.org/10.1007/978-3-030-21507-1_45
• topic: Breast Cancer; Neoadjuvant Chemotherapy; Knowledge Representation and Reasoning; Case Based Reasoning; Entropy; Logic Programming

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.