Detection of ECG Arrhythmia using a differential expert system approach based on principal component analysis and least square support vector machine
Tài liệu tham khảo
N. Cheung, Machine learning techniques for medical analysis, School of Information Technology and Electrical Engineering, BSc thesis, University of Queenland, 2001.
Piatetsky-Shapiro, 1991
Michie, 1991, Methodologies from Machine Learning in Data Analysis and Software, Computer Journal, 34, 559, 10.1093/comjnl/34.6.559
Fayyad, 1996
M. Embrechts, B. Szymanski, K. Sternickel, T. Naenna, R. Bragaspathi, Use of Machine Learning for Classification of Magnetocardiograms, in: Proc. IEEE Conference on System, Man and Cybernetics. Washington, DC, 2003, pp. 1400–1405.
Pazzani, 1992, The Utility of Knowledge in Inductive Learning, Machine Learning, 9, 57, 10.1007/BF00993254
ECG Arrhythmia Dataset. UCI Repository of Machine Learning Databases. Available from: <ftp://ftp.ics.uci.edu/pub/machine-learning-databases/> (accessed July 2006).
Bortolan, 2002, An interactive framework for an analysis of ECG signals, Artificial Intelligence in Medicine, 24, 109, 10.1016/S0933-3657(01)00096-3
de la Calleja, 2004, Machine learning and image analysis for morphological galaxy classification, Monthly Notices of the Royal Astronomical Society, 349, 87, 10.1111/j.1365-2966.2004.07442.x
Wang, 2003, Feature extraction and dimensionality reduction algorithms and their applications in vowel recognition, Pattern Recognition. The Journal of The Pattern Recognition Society, 36, 2429, 10.1016/S0031-3203(03)00044-X
Lindsay, I. Smith, A tutorial on principal components analysis. Available from: <http://kybele.psych.cornell.edu/~edelman/Psych-465Spring-2003/PCA-tutorial>, 2002.
Vapnik, 1995
Suykens, 1999, Least squares support vector machine classifiers, Neural Processing Letters, 9, 293, 10.1023/A:1018628609742
Daisuke, 2003, 16
Fawcett, 2006, An introduction to ROC analysis, Pattern Recognition Letters, 27, 861, 10.1016/j.patrec.2005.10.010
Osareh, 2002, Comparative exudate classification using support vector machines and neural networks, vol. 2489, 413
Centor, 1991, Signal Detectability: The use of ROC Curves and their Analysis, Medical Decision Making, 11, 102, 10.1177/0272989X9101100205
