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تشخیص اختلال طیف اوتیسم براساس ویژگی‌های شبکه پیچیده

عنوان انگلیسی: Diagnosis of autism spectrum disorder based on complex network features
سال نشر: ۲۰۱۹
نویسنده: Ghasem Sadeghi Bajestani,Mahboobe Behrooz,Adel Ghazi Khani,Mostafa Nouri-Baygi,Ali Mollaei
تعداد صفحه فارسی: ۱ – تعداد صفحه انگلیسی: ۱۷
دانشگاه: Center for Computational Neuroscience Research, Department of Biomedical Engineering, Imam Reza International University, Mashhad, Razavi Khorasan, Iran b Software Department, Computer Engineering Faculty, Imam Reza International University, Mashhad, Iran c Computer Engineering Department, Imam Reza International University, Mashhad, Iran d Computer Engineering Department, Ferdowsi University, Mashhad, Iran e Artificial Intelligence Department, Computer Engineering Faculty, Islamic Azad Universi
نشریه: Process Safety and Environmental Protection
کیفیت ترجمه: اقتصادی


زمینه و اهداف : اختلال طیف اوتیسم (‏ ASD )‏ اختلال در جریان اطلاعات سیستم مغز انسان است که می‌تواند منجر به مشکلات ثانویه برای بیمار شود . تنها زمانی اختلال طیف اوتیسم با روش‌های بالینی تشخیص داده می‌شود، می توان مشکلات ثانویه را تشخیص داد. از این رو , تشخیص اختلال طیف اوتیسم در سنین پایین و در کودکان خردسال می‌تواند از اثرات ثانویه آن پیش‌گیری کند .


Highlight•ASD diagnosis at an early age and in childhood has a large impact on improving case studies.•The complex networks features from the brain signals can help to ASD diagnosis.•This method can be used in pre-primary screening.AbstractBackground and ObjectivesAutism spectrum disorder (ASD) is a disorder in the information flow of the human brain system that can lead to secondary problems for the patient. Only when ASD is diagnosed by clinical methods can the secondary problems be detected. Hence, diagnosis of ASD at an early age and in young children can prevent its secondary effects.MethodsBy employing the visibility graph (VG) algorithm, the present study examines the C3 single-channel of EEG signals and presents the differences among the topological features of complex networks resulting from these signals. The average degree (AD) can be a method for the detection of normal and ASD samples.ResultsWith an accuracy 81/67%, the ASD class can be discerned.ConclusionsThe current pap
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