کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4335013 | 1295114 | 2013 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Standardized database development for EEG epileptiform transient detection: EEGnet scoring system and machine learning analysis
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب (عمومی)
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چکیده انگلیسی
⺠We describe our new web-based software for collecting expert opinion on paroxysmal activity in routine scalp EEG. ⺠We report that inter-rater correlation among our groups of 11 board-certified EEG scorers was only moderate. ⺠Our machine learning analysis suggests that our EEG database needs to be larger than its current size to adequately represent the variability of waveform morphologies in EEG. ⺠Our artificial neural network machine learning classifiers performed better than our Bayesian classifiers and the wavelet features were the most useful.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 212, Issue 2, 30 January 2013, Pages 308-316
Journal: Journal of Neuroscience Methods - Volume 212, Issue 2, 30 January 2013, Pages 308-316
نویسندگان
Jonathan J. Halford, Robert J. Schalkoff, Jing Zhou, Selim R. Benbadis, William O. Tatum, Robert P. Turner, Saurabh R. Sinha, Nathan B. Fountain, Amir Arain, Paul B. Pritchard, Ekrem Kutluay, Gabriel Martz, Jonathan C. Edwards, Chad Waters,