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A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.
Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang.
Afiliación
  • Peng B; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China; University of Chinese Academy of Sciences, Beijing 100049, China; Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, Ch
  • Wang S; Department of Neuroscience, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu 213003, China.
  • Zhou Z; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
  • Liu Y; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
  • Tong B; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
  • Zhang T; Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, China.
  • Dai Y; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China. Electronic address: daiyk@sibet.ac.cn.
Neurosci Lett ; 651: 88-94, 2017 06 09.
Article en En | MEDLINE | ID: mdl-28435046
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Encéfalo / Mapeo Encefálico / Aprendizaje Automático Tipo de estudio: Diagnostic_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: Neurosci Lett Año: 2017 Tipo del documento: Article País de afiliación: Suiza
Texto completo
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PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Encéfalo / Mapeo Encefálico / Aprendizaje Automático Tipo de estudio: Diagnostic_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: Neurosci Lett Año: 2017 Tipo del documento: Article País de afiliación: Suiza