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Title: Logic Programming and Artificial Neural Networks in Breast Cancer Detection
Authors: Neves, José
Guimarães, Tiago
Gomes, Sabino
Vicente, Henrique
Santos, Mariana
Neves, João
Machado, José
Novais, Paulo
Editors: Rojas, Ignacio
Joya, Gonzalo
Catala, Andreu
Keywords: Breast Cancer
Tyrer-Cuzick Model
Knowledge Representation and Reasoning
Logic Programing
Artificial Neural Networks
Issue Date: 2015
Publisher: Springer International Publishing
Citation: Neves, J., Guimarães, T., Gomes, S., Vicente, H., Santos, M., Neves, J., Machado, J. & Novais, P., Logic Programming and Artificial Neural Networks in Breast Cancer Detection. In I. Rojas, G. Joya & A. Catala, Eds., Advances in Computational Intelligence – Part II, Lecture Notes on Computer Science, Vol. 9095, pp. 211–224, Springer International Publishing, Cham, Switzerland, 2015.
Abstract: About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.
ISBN: 978-3-319-19221-5
Type: bookPart
Appears in Collections:CQE - Publicações - Capítulos de Livros
QUI - Publicações - Capítulos de Livros

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