Predicative Vagueness in Lung Metastases in Soft Tissue Sarcoma Screening

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 prof...

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Detalhes bibliográficos
Autor principal: Neves, José (author)
Outros Autores: Dias, Almeida (author), Morais, Ana (author), Fonseca, Francisca (author), Loreto, Patrícia (author), Alves, Victor (author), Araújo, Isabel (author), Machado, Joana (author), Fernandes, Bruno (author), Ribeiro, Jorge (author), Analide, César (author), Ferraz, Filipa (author), Neves, João (author), Vicente, Henrique (author)
Formato: article
Idioma:eng
Publicado em: 2019
Assuntos:
Soft Tissue Sarcoma
Magnetic Resonance Imaging
Logic Programming
Knowledge Representation and Reasoning
Case Based Reasoning
Entropy
Predicative Vagueness
Texto completo:http://hdl.handle.net/10174/25419
País:Portugal
Oai:oai:dspace.uevora.pt:10174/25419
Descrição
Resumo: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.

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