Deep learning-aided Parkinson's disease diagnosis from handwritten dynamics

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Federal de São Carlos (UFSCar)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorOstbayerische Tech. Hochschule-
Autor(es): dc.creatorPereira, Clayton R.-
Autor(es): dc.creatorWeber, Silke A.T.-
Autor(es): dc.creatorHook, Christian-
Autor(es): dc.creatorRosa, Gustavo H.-
Autor(es): dc.creatorPapa, Joao P.-
Data de aceite: dc.date.accessioned2025-08-21T15:24:30Z-
Data de disponibilização: dc.date.available2025-08-21T15:24:30Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2017-01-10-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/SIBGRAPI.2016.054-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/232575-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/232575-
Descrição: dc.descriptionParkinson's Disease (PD) automatic identification in early stages is one of the most challenging medicine-related tasks to date, since a patient may have a similar behaviour to that of a healthy individual at the very early stage of the disease. In this work, we cope with PD automatic identification by means of a Convolutional Neural Network (CNN), which aims at learning features from a signal extracted during the individual's exam by means of a smart pen composed of a series of sensors that can extract information from handwritten dynamics. We have shown CNNs are able to learn relevant information, thus outperforming results obtained from raw data. Also, this work aimed at building a public dataset to be used by researchers worldwide in order to foster PD-related research.-
Descrição: dc.descriptionDepartment of Computing Federal University of São Carlos-
Descrição: dc.descriptionMedical School of Botucatu São Paulo State University-
Descrição: dc.descriptionFakultät Informatik/Mathematik Ostbayerische Tech. Hochschule-
Descrição: dc.descriptionDepartment of Computing São Paulo State University-
Descrição: dc.descriptionMedical School of Botucatu São Paulo State University-
Descrição: dc.descriptionDepartment of Computing São Paulo State University-
Formato: dc.format340-346-
Idioma: dc.languageen-
Relação: dc.relationProceedings - 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2016-
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Palavras-chave: dc.subjectConvolutional Neural Networks-
Palavras-chave: dc.subjectParkinson's Disease-
Título: dc.titleDeep learning-aided Parkinson's disease diagnosis from handwritten dynamics-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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