Machine Learning
Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Support Vector Machines for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Assessment of the classification capability of prediction and approximation methods for HRV analysis
Computers in Biology and Medicine
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Multiclass Support Vector Machines for EEG-Signals Classification
IEEE Transactions on Information Technology in Biomedicine
On combining support vector machines and simulated annealing in stereovision matching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Fusing images with different focuses using support vector machines
IEEE Transactions on Neural Networks
Introduction to the special section on computationalintelligence in medical systems
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Mining physiological conditions from heart rate variability analysis
IEEE Computational Intelligence Magazine
ITBAM'10 Proceedings of the First international conference on Information technology in bio- and medical informatics
Active learning methods for electrocardiographic signal classification
IEEE Transactions on Information Technology in Biomedicine
Computers in Biology and Medicine
Patient Outcome Prediction with Heart Rate Variability and Vital Signs
Journal of Signal Processing Systems
Superiority real-time cardiac arrhythmias detection using trigger learning method
ITBAM'11 Proceedings of the Second international conference on Information technology in bio- and medical informatics
Heart beat classification using wavelet feature based on neural network
WSEAS TRANSACTIONS on SYSTEMS
Expert Systems with Applications: An International Journal
Life-logging of wheelchair driving on web maps for visualizing potential accidents and incidents
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Engineering Applications of Artificial Intelligence
Classifying heart sounds using multiresolution time series motifs: an exploratory study
Proceedings of the International C* Conference on Computer Science and Software Engineering
Biomedical time series clustering based on non-negative sparse coding and probabilistic topic model
Computer Methods and Programs in Biomedicine
Finding time series discord based on bit representation clustering
Knowledge-Based Systems
| Hi-index | 0.00 |
In this study, heartbeat time series are classified using support vector machines (SVMs). Statistical methods and signal analysis techniques are used to extract features from the signals. The SVMclassifier is favorably compared to other neural network-based classification approaches by performing leave-one-out cross validation. The performance of the SVM with respect to other state-of-the-art classifiers is also confirmed by the classification of signals presenting very low signal-to-noise ratio. Finally, the influence of the number of features to the classification rate was also investigated for two real datasets. The first dataset consists of long-term ECG recordings of young and elderly healthy subjects. The second dataset consists of long-termECGrecordings of normal subjects and subjects suffering from coronary artery disease.