Machine learning: applications in expert systems and information retrieval
Machine learning: applications in expert systems and information retrieval
C4.5: programs for machine learning
C4.5: programs for machine learning
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Mining biosignal data: coronary artery disease diagnosis using linear and nonlinear features of HRV
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
| Hi-index | 0.00 |
Currently, many researches have been pursued for cardiovascular disease diagnosis using ECG so far. In this paper we extract multi-parametric features by HRV analysis from ECG, data preprocessing and heart disease pattern classification method. This study analyzes the clinical information as well as the time and the frequency domains of HRV, and then discovers cardiovascular disease patterns of patient groups. In each group, its patterns are a large frequency in one class, patients with coronary artery disease but are never found in the control or normal group. These patterns are called emerging patterns. We also use efficient algorithms to derive the patterns using the cohesion measure. Our studies show that the discovered patterns from 670 participants are used to classify new instances with higher accuracy than other reported methods