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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Bibliographic Details
Main Author: Neves, José (author)
Other Authors: Dias, Almeida (author), Morais, Ana (author), Fonseca, Francisca (author), Loreto, Patrícia (author), Alves, Victor (author), Araújo, Isabel (author), Machado, Joana (author), Fernandes, B. (author), Ribeiro, Jorge (author), Analide, Cesar (author), Ferraz, Filipa Tinoco (author), Neves, João (author), Vicente, Henrique (author)
Format: conferencePaper
Language:eng
Published: 2018
Subjects:
Case Based Reasoning
Entropy
Knowledge Representation and Reasoning
Logic Programming
Magnetic Resonance Imaging
Predicative Vagueness
Soft Tissue Sarcoma
Online Access:http://hdl.handle.net/1822/71384
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/71384
Description
Summary: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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