Art

J-GLOBAL ID：202002289477121402   Reference number：20A0980118

A robust method for early diagnosis of autism spectrum disorder from EEG signals based on feature selection and DBSCAN method

特徴選択とDBSCAN法に基づくEEG信号からの自閉症スペクトラム障害の早期診断のためのロバストな方法【JST・京大機械翻訳】

Author (3)： Abdolzadegan Donya (Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran) ,  Moattar Mohammad Hossein (Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran) ,  Ghoshuni Majid (Department of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran)
Material： Biocybernetics and Biomedical Engineering
Volume： 40  Issue： 1  Page： 482-493  Publication year： 2020 
JST Material Number： W3437A  ISSN： 0208-5216  Document type： Article
Article type： 原著論文  Country of issue： Netherlands (NLD)  Language： ENGLISH (EN)

Abstract/Point： Electroencephalogram (EEG) is ...

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Thesaurus term： entropy ,  redundancy(property) ,  electroencephalogram ,  clustering ,  *feature selection ,  child ,  power spectrum ,  *autism ,  fractal dimension ,  *robustness ,  *early diagnosis ,  artifact ,  wavelet transform ,  support vector machine
Semi thesaurus term： 尤度 , 【Automatic Indexing@JST】

Author keywords (7)： Electroencephalography ,  Autism spectrum disorder ,  Feature extraction ,  Correlation dimension ,  Lyapunov exponent ,  Density based clustering ,  Feature selection

JST classification (4)： Psychiatric diagnosis  (GR02000T) ,  Clinical psychiatry in general  (GR01030T) ,  Neurologic diagnosis  (GN02000H) ,  Mental disorders  (GR03000A)

Terms in the title (5)： 特徴選択 ,  EEG信号 ,  自閉症スペクトラム障害 ,  早期診断 ,  ロバスト