Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/19698

Title: A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection
Authors: Esteves, Marisa
Vicente, Henrique
Machado, José
Alves, Victor
Neves, José
Editors: Herawan, Tutut
Ghazali, Rozaida
Nawi, Nazri M.
Deris, Mustafa M.
Keywords: Knee Osteoarthritis
Knee X-Ray
Image Feature Extraction
Knowledge Representation and Reasoning
Logic Programming
Case-Based Reasoning
Issue Date: 2017
Publisher: Springer International Publishing
Citation: Esteves, M., Vicente, H., Machado, J., Alves, V. & Neves, J., A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection. In T. Herawan, R. Ghazali, N. M. Nawi & M. M. Deris, Eds., Recent Advances on Soft Computing and Data Mining, Advances in Intelligent Systems and Computing, Vol. 549, pp. 274–284, Springer International Publishing, Cham, Switzerland, 2017.
Abstract: Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.
URI: http://link.springer.com/chapter/10.1007/978-3-319-51281-5_28
http://hdl.handle.net/10174/19698
ISBN: 978-3-319-51279-2
ISSN: 2194-5357
Type: bookPart
Appears in Collections:QUI - Publicações - Capítulos de Livros

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