Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/39024

TitleAbstract computation in schizophrenia detection through artificial neural network based systems
Author(s)Cardoso, L.
Marins, F.
Magalhães, R.
Marins, N.
Oliveira, T.
Vicente, H.
Abelha, António
Machado, José Manuel
Neves, J.
Issue date2015
PublisherHindawi Publishing Corporation
JournalScientific World Journal
CitationCardoso, L., Marins, F., Magalhães, R., Marins, N., Oliveira, T., Vicente, H., . . . Neves, J. (2015). Abstract computation in schizophrenia detection through artificial neural network based systems. Scientific World Journal, 2015. doi: 10.1155/2015/467178
Abstract(s)Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.
TypeArticle
URIhttp://hdl.handle.net/1822/39024
DOI10.1155/2015/467178
ISSN2356-6140
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CCTC - Artigos em revistas internacionais
DI/CCTC - Artigos (papers)

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