Nonlinear Weighting Ensemble Learning Model to Diagnose Parkinson's Disease Using Multimodal Data.

Castillo-Barnes, D; Martinez-Murcia, F J; Jimenez-Mesa, C; Arco, J E; Salas-Gonzalez, D; Ramírez, J; Górriz, J M

Castillo-Barnes, D; Martinez-Murcia, F J; Jimenez-Mesa, C; Arco, J E; Salas-Gonzalez, D; Ramírez, J; Górriz, J M.

Afiliação

Castillo-Barnes D; Department of Communications Engineering, University of Malaga, Blvr. Louis Pasteur 35 29004, Malaga, Spain.
Martinez-Murcia FJ; Department of Signal Theory, Telematics and Communications, University of Granada, Periodista Daniel Saucedo Aranda S/N 18071, Granada, Spain.
Jimenez-Mesa C; Department of Signal Theory, Telematics and Communications, University of Granada, Periodista Daniel Saucedo Aranda S/N 18071, Granada, Spain.
Arco JE; Department of Communications Engineering, University of Malaga, Blvr. Louis Pasteur 35 29004, Malaga, Spain.
Salas-Gonzalez D; Department of Signal Theory, Telematics and Communications, University of Granada, Periodista Daniel Saucedo Aranda S/N 18071, Granada, Spain.
Ramírez J; Department of Signal Theory, Telematics and Communications, University of Granada, Periodista Daniel Saucedo Aranda S/N 18071, Granada, Spain.
Górriz JM; Department of Signal Theory, Telematics and Communications, University of Granada, Periodista Daniel Saucedo Aranda S/N 18071, Granada, Spain.

Int J Neural Syst ; 33(8): 2350041, 2023 Aug.

Article em En | MEDLINE | ID: mdl-37470777

Assuntos

Doença de Parkinson; Adulto; Humanos; Doença de Parkinson/diagnóstico; Aprendizado de Máquina; Diagnóstico por Computador; Imageamento por Ressonância Magnética/métodos

Palavras-chave

Ensemble learning; MRI; Parkinson's disease; SPECT; computer-aided-diagnosis; image processing; machine learning; neuroimaging

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença de Parkinson Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adult / Humans Idioma: En Revista: Int J Neural Syst Assunto da revista: ENGENHARIA BIOMEDICA / INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Espanha

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