کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6853627 | 1437211 | 2016 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Classification of epilepsy using computational intelligence techniques
ترجمه فارسی عنوان
طبقه بندی صرع با استفاده از تکنیک های هوش مصنوعی
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کلمات کلیدی
Epilepsy classificationNaïve Bayes - Bayes نائومیK-means clustering - K به معنی خوشه بندی استFeature extraction - استخراج ویژگیDiscrete wavelet transform - تبدیل موجک گسستهAbsence seizure - تشنج عدم وجودNeural networks - شبکه های عصبیSupport vector machines - ماشین بردار پشتیبانیk-nearest neighbours - نزدیک ترین همسایگان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
This paper deals with a real-life application of epilepsy classification, where three phases of absence seizure, namely pre-seizure, seizure and seizure-free, are classified using real clinical data. Artificial neural network (ANN) and support vector machines (SVMs) combined with supervised learning algorithms, and k-means clustering (k-MC) combined with unsupervised techniques are employed to classify the three seizure phases. Different techniques to combine binary SVMs, namely One Vs One (OvO), One Vs All (OvA) and Binary Decision Tree (BDT), are employed for multiclass classification. Comparisons are performed with two traditional classification methods, namely, k-Nearest Neighbour (k-NN) and Naive Bayes classifier. It is concluded that SVM-based classifiers outperform the traditional ones in terms of recognition accuracy and robustness property when the original clinical data is distorted with noise. Furthermore, SVM-based classifier with OvO provides the highest recognition accuracy, whereas ANN-based classifier overtakes by demonstrating maximum accuracy in the presence of noise.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: CAAI Transactions on Intelligence Technology - Volume 1, Issue 2, April 2016, Pages 137-149
Journal: CAAI Transactions on Intelligence Technology - Volume 1, Issue 2, April 2016, Pages 137-149
نویسندگان
Khurram I. Qazi, H.K. Lam, Bo Xiao, Gaoxiang Ouyang, Xunhe Yin,