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Alzheimer’s early prediction with electroencephalogram

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Detalhes bibliográficos
Resumo:Alzheimer's disease (AD) is currently an incurable illness that causes dementia and patienfs condition is progressively worse and it represents one ofthe greatest public health challenges worldwide. The main objective ofthis work was to develop a classificatiwmethodology for EEG signals to improve discrimination amongst patients at varying stages ofthe illness, Mitd Cognitive Impairment (MCI) patients and non-patients either in order to obtain a more reliable methodology to identify AD in early stages.
Autores principais:Rodrigues, Pedro Miguel
Outros Autores:Teixeira, João Paulo; Garrett, Carolina; Alves, Dílio; Freitas, Diamantino Silva
Assunto:Alzheimer diasease Early stages Electroencephalogram signal Surrogate decision tree classifier
Ano:2016
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:Alzheimer's disease (AD) is currently an incurable illness that causes dementia and patienfs condition is progressively worse and it represents one ofthe greatest public health challenges worldwide. The main objective ofthis work was to develop a classificatiwmethodology for EEG signals to improve discrimination amongst patients at varying stages ofthe illness, Mitd Cognitive Impairment (MCI) patients and non-patients either in order to obtain a more reliable methodology to identify AD in early stages.