Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/52164
Título: | A knowledge representation and reasoning system for multimodal neuroimaging studies |
Autor(es): | Coelho, Ana Marques, Paulo César Gonçalves Magalhães, Ricardo José Silva Sousa, Nuno Neves, José Alves, Victor |
Palavras-chave: | Artificial intelligence Case-based reasoning Multimodal neuroimaging |
Data: | 2017 |
Editora: | Iberoamerican Society of Artificial Intelligence (IBERAMIA) |
Revista: | Inteligencia Artificial |
Resumo(s): | Multimodal neuroimaging analyses are of major interest for both research and clinical practice, enabling the combined evaluation of the structure and function of the human brain. These analyses generate large volumes of data and consequently increase the amount of possibly useful information. Indeed, BrainArchive was developed in order to organize, maintain and share this complex array of neuroimaging data. It stores all the information available for each participant/patient, being dynamic by nature. Notably, the application of reasoning systems to this multimodal data has the potential to provide tools for the identification of undiagnosed diseases. As a matter of fact, in this work we explore how Artificial Intelligence techniques for decision support work, namely Case-Based Reasoning (CBR) that may be used to achieve such endeavour. Particularly, it is proposed a reasoning system that uses the information stored in BrainArchive as past knowledge for the identification of individuals that are at risk of contracting some brain disease. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/52164 |
DOI: | 10.4114/intartif.vol20iss59pp42-52 |
ISSN: | 1137-3601 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals ICVS - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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document.pdf Acesso restrito! | 1,32 MB | Adobe PDF | Ver/Abrir |