Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/25562

Title: Predicting Diabetic Foot Maturing Through Evolutionary Computation
Authors: Neves, José
Alves, André
Prata, Marco
Ribeiro, Mário
Alves, Victor
Ferraz, Filipa
Neves, João
Ribeiro, Jorge
Capita, António
Vicente, Henrique
Keywords: Diabetic Mellitus
Case-Based Reasoning
Artificial Neural Networks
ImageJ
Many-Valued Machines
Issue Date: 2019
Publisher: Springer
Citation: Neves, J., Alves, A., Prata, M., Ribeiro, M., Alves, V., Ferraz, F., Neves, J., Ribeiro, J., Capita, A. & Vicente, H.,Predicting Diabetic Foot Maturing through Evolutionary Computation. Advances in Intelligent Systems and Computing, 75, 109-117, 2019.
Abstract: It is a twenty-first-century disease, its numbers are still growing exponentially. This brings one to the subject of this work, the Maturing of Diabetic Foot which, like diabetes, rises to values never seen before. It is envisaging the development of an ImageJ plug-into extract relevant feature from diabetic foot images and, in conjunction with the patient's clinical and lifelong data, a computational system to predict and evaluate its severity. The applied problem-solving method is based on a symbolic/sub-symbolic line of logical formalisms that make complex systems easier to develop and analyze, where solutions to new problems are based on answers to previous ones, and itemized as a Case-Based Reasoning/Artificial Neural Network approach to computing.
URI: https://link.springer.com/chapter/10.1007/978-981-13-7150-9_11
http://hdl.handle.net/10174/25562
ISSN: 2367-3370 (paper)
2367-3389 (electronic)
Type: article
Appears in Collections:QUI - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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