Bag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorUniversidade Federal de São Carlos (UFSCar)-
Autor(es): dc.creatorRibeiro, Luiz C.F. [UNESP]-
Autor(es): dc.creatorAfonso, Luis C.S.-
Autor(es): dc.creatorPapa, João P. [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:32:54Z-
Data de disponibilização: dc.date.available2022-02-22T00:32:54Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-11-30-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.compbiomed.2019.103477-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/201208-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/201208-
Descrição: dc.descriptionParkinson's Disease (PD) is a clinical syndrome that affects millions of people worldwide. Although considered as a non-lethal disease, PD shortens the life expectancy of the patients. Many studies have been dedicated to evaluating methods for early-stage PD detection, which includes machine learning techniques that employ, in most cases, motor dysfunctions, such as tremor. This work explores the time dependency in tremor signals collected from handwriting exams. To learn such temporal information, we propose a model based on Bidirectional Gated Recurrent Units along with an attention mechanism. We also introduce the concept of “Bag of Samplings” that computes multiple compact representations of the signals. Experimental results have shown the proposed model is a promising technique with results comparable to some state-of-the-art approaches in the literature.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionUNESP - São Paulo State University School of Sciences-
Descrição: dc.descriptionUFSCar - Federal University of São Carlos Department of Computing-
Descrição: dc.descriptionUNESP - São Paulo State University School of Sciences-
Descrição: dc.descriptionFAPESP: 2013/07375-0-
Descrição: dc.descriptionFAPESP: 2014/12236-1-
Descrição: dc.descriptionCNPq: 307066/2017-7-
Descrição: dc.descriptionCNPq: 427968/2018-6-
Idioma: dc.languageen-
Relação: dc.relationComputers in Biology and Medicine-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectBag of samplings-
Palavras-chave: dc.subjectHandwritten dynamics-
Palavras-chave: dc.subjectParkinson's disease-
Palavras-chave: dc.subjectRecurrent Neural Networks-
Título: dc.titleBag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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