Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy
المؤلفون المشاركون
Ahmad, Malik Anas
Ayaz, Yasar
Jamil, Mohsin
Omer Gillani, Syed
Rasheed, Muhammad Babar
Imran, Muhammad
Khan, Nadeem Ahmed
Majeed, Waqas
Javaid, N.
المصدر
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-03-05
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Computer-assisted analysis of electroencephalogram (EEG) has a tremendous potential to assist clinicians during the diagnosis of epilepsy.
These systems are trained to classify the EEG based on the ground truth provided by the neurologists.
So, there should be a mechanism in these systems, using which a system’s incorrect markings can be mentioned and the system should improve its classification by learning from them.
We have developed a simple mechanism for neurologists to improve classification rate while encountering any false classification.
This system is based on taking discrete wavelet transform (DWT) of the signals epochs which are then reduced using principal component analysis, and then they are fed into a classifier.
After discussing our approach, we have shown the classification performance of three types of classifiers: support vector machine (SVM), quadratic discriminant analysis, and artificial neural network.
We found SVM to be the best working classifier.
Our work exhibits the importance and viability of a self-improving and user adapting computer-assisted EEG analysis system for diagnosing epilepsy which processes each channel exclusive to each other, along with the performance comparison of different machine learning techniques in the suggested system.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ahmad, Malik Anas& Ayaz, Yasar& Jamil, Mohsin& Omer Gillani, Syed& Rasheed, Muhammad Babar& Imran, Muhammad…[et al.]. 2015. Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy. BioMed Research International،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1056231
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ahmad, Malik Anas…[et al.]. Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy. BioMed Research International No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1056231
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ahmad, Malik Anas& Ayaz, Yasar& Jamil, Mohsin& Omer Gillani, Syed& Rasheed, Muhammad Babar& Imran, Muhammad…[et al.]. Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1056231
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1056231
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر