Author(s):
Neves, José ; Dias, Almeida ; Morais, Ana ; Fonseca, Francisca ; Loreto, Patrícia ; Alves, Victor ; Araújo, Isabel ; Machado, Joana ; Fernandes, Bruno ; Ribeiro, Jorge ; Analide, César ; Ferraz, Filipa ; Neves, João ; Vicente, Henrique
Date: 2019
Persistent ID: http://hdl.handle.net/10174/25419
Origin: Repositório Científico da Universidade de Évora
Subject(s): Soft Tissue Sarcoma; Magnetic Resonance Imaging; Logic Programming; Knowledge Representation and Reasoning; Case Based Reasoning; Entropy; Predicative Vagueness
Description
Soft Tissue Sarcomas (STSs) pose a potential risk for the development of lung metastases, which in turn results in a negative prognosis for patients. Presumptions about the occurrence of these abnormalities during STSs treatment would have countless implications for both patients and healthcare professionals as they could increase the efficacy of the treatment and improve overall survival. Prediction is based on a creative Logic Programming, Case Based Reasoning approach to problem solving, that is complemented with an unusual approach to Knowledge Representation and Reasoning, as it takes into consideration not only the data items entropic states but introduces the concept of Vague's Predicate Extension.
