A Data Mining Approach for Coronary Heart Disease Prediction using HRV Features and Carotid Arterial Wall Thickness

Automated diagnosis of Coronary Artery Disease affected patients using LDA, PCA, ICA and Discrete Wavelet Transform

“…SVM presented the highest accuracy of almost 90% using features from all three recumbent positions. Using a similar set of features, the same group [34] obtained a classification accuracy of 88.33% for the classification of normal, AP, and ACS classes. They included the carotid arterial wall thickness in addition to HRV features and observed a classification accuracy of around 85-90% for Classification based on Predictive Association Rules (CPAR) and SVM classifiers.…”

“…Karimi et al [26] Wavelet analysis Neural network 85 Arafat et al [6] ECG Stress Signals with Probabilistic Neural Networks Fuzzy Inference Systems 80 Lee et al [33] Linear and Nonlinear Parameters SVM Classifier 90 Kim et al [30] Multiple Discriminant Analysis with linear and non linear feature Different Classifiers 72.5-84.6 Zhao and Ma [46] Emperical Mode Decomposition-Teager Energy Operator Back Propagation Neural Network 85 Lee et al [34] HRV, carotid arterial wall thickness CPAR and SVM 85-90 Babaoglu et al [7] Binary Particle Swarm Optimization SVM 81.46 Babaoglu et al [8] PCA for dimension reduction SVM 79.71 In this work HRV signals and ICA GMM 96.8…”

Data Mining, Soft Computing, Machine Learning and BioInspired Computing for Heart Disease Classification/ Prediction – A Review

“…Lee et al in [1] and [2] proposed a unique methodology to develop the various features of heart rate variability (HRV) and carotid arterial wall thickness. They had also proposed a prediction model to improve the reliability of medical examinations and treatments for cardiovascular disease.…”

“…As a result, CPAR and SVM (gave about 85%-90% goodness of fit) outperforming the other classifiers. In their another work in [2], various experiments on linear and nonlinear features of HRV to evaluate classifiers were conducted and from their experiments, the authors claimed that SVM and Bayesian classifiers outperformed the other classifiers.…”

Medical Decision Support System of Common Carotid Artery Using Image Mining and Dual Snake Segmentation Procedure

“…It is employed to detect the similarity between the images in a quick timely manner 8,9 . It was the procedure of mining association rules in database of transactions between items.…”