Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/71388
Título: | Predicting diabetic foot maturing through evolutionary computation |
Autor(es): | Neves, José Alves, André Prata, Marco Ribeiro, Mário Alves, Victor Ferraz, Filipa Tinoco Neves, João Ribeiro, Jorge Capita, António Vicente, Henrique |
Palavras-chave: | Artificial neural networks Case-based reasoning Diabetic mellitus ImageJ Many-valued machines |
Data: | 2019 |
Editora: | Springer |
Revista: | Lecture Notes in Networks and Systems |
Citação: | Neves J. et al. (2019) Predicting Diabetic Foot Maturing Through Evolutionary Computation. In: Peng SL., Dey N., Bundele M. (eds) Computing and Network Sustainability. Lecture Notes in Networks and Systems, vol 75. Springer, Singapore. https://doi.org/10.1007/978-981-13-7150-9_11 |
Resumo(s): | 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. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/71388 |
ISBN: | 978-981-13-7149-3 |
e-ISBN: | 978-981-13-7150-9 |
DOI: | 10.1007/978-981-13-7150-9_11 |
ISSN: | 2367-3370 |
Versão da editora: | https://link.springer.com/chapter/10.1007%2F978-981-13-7150-9_11 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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4.pdf Acesso restrito! | 243,63 kB | Adobe PDF | Ver/Abrir |