Use of neural networks in predicting the risk of coronary artery disease
Computers and Biomedical Research
Machine Learning
MultiBoosting: A Technique for Combining Boosting and Wagging
Machine Learning
Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF
Applied Intelligence
Decision Trees: An Overview and Their Use in Medicine
Journal of Medical Systems
An introduction to variable and feature selection
The Journal of Machine Learning Research
A Bayesian Approach to Joint Feature Selection and Classifier Design
IEEE Transactions on Pattern Analysis and Machine Intelligence
MBNR: Case-Based Reasoning with Local Feature Weighting by Neural Network
Applied Intelligence
Sparse Multinomial Logistic Regression: Fast Algorithms and Generalization Bounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast Dual Algorithm for Kernel Logistic Regression
Machine Learning
Temporal reasoning for decision support in medicine
Artificial Intelligence in Medicine
Rotation Forest: A New Classifier Ensemble Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Computer Methods and Programs in Biomedicine
CoViCAD: Comprehensive Visualization of Coronary Artery Disease
IEEE Transactions on Visualization and Computer Graphics
Exploiting missing clinical data in Bayesian network modeling for predicting medical problems
Journal of Biomedical Informatics
Journal of Biomedical Informatics
Cancer classification using Rotation Forest
Computers in Biology and Medicine
Artificial Intelligence in Medicine
Expert Systems with Applications: An International Journal
Boosting and measuring the performance of ensembles for a successful database marketing
Expert Systems with Applications: An International Journal
A model for dynamic object segmentation with kernel density estimation based on gradient features
Image and Vision Computing
Boosting k-nearest neighbor classifier by means of input space projection
Expert Systems with Applications: An International Journal
Gaussian process approach for modelling of nonlinear systems
Engineering Applications of Artificial Intelligence
Learning from imbalanced data in surveillance of nosocomial infection
Artificial Intelligence in Medicine
Gene extraction for cancer diagnosis by support vector machines-An improvement
Artificial Intelligence in Medicine
Bio-medical entity extraction using support vector machines
Artificial Intelligence in Medicine
Pattern recognition techniques for automatic detection of suspicious-looking anomalies in mammograms
Computer Methods and Programs in Biomedicine
Impact of censoring on learning Bayesian networks in survival modelling
Artificial Intelligence in Medicine
Bayesian Online Multitask Learning of Gaussian Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boosting with pairwise constraints
Neurocomputing
Software reliability assessment using artificial neural network
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Sparse Multiple Kernel Learning for Signal Processing Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cost-sensitive boosting neural networks for software defect prediction
Expert Systems with Applications: An International Journal
Mathematical modeling of software reliability testing with imperfect debugging
Computers & Mathematics with Applications
Assessment of the risk factors of coronary heart events based on data mining with decision trees
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
Boosting a multi-linear classifier with application to visual lip reading
Expert Systems with Applications: An International Journal
IEEE Transactions on Image Processing
A decision support system for cost-effective diagnosis
Artificial Intelligence in Medicine
Comparing performances of backpropagation and genetic algorithms in the data classification
Expert Systems with Applications: An International Journal
Artificial Intelligence in Medicine
Expert Systems with Applications: An International Journal
Cost-sensitive case-based reasoning using a genetic algorithm: Application to medical diagnosis
Artificial Intelligence in Medicine
Incorporating expert knowledge when learning Bayesian network structure: A medical case study
Artificial Intelligence in Medicine
QBoost: Predicting quantiles with boosting for regression and binary classification
Expert Systems with Applications: An International Journal
Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions
Computational Statistics & Data Analysis
Computer Methods and Programs in Biomedicine
Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence in Medicine
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Automated Diagnosis of Coronary Artery Disease Based on Data Mining and Fuzzy Modeling
IEEE Transactions on Information Technology in Biomedicine
Predicting Breast Screening Attendance Using Machine Learning Techniques
IEEE Transactions on Information Technology in Biomedicine
Evolutionary optimization of radial basis function classifiers for data mining applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Model-based interpretation of cardiac beats by evolutionary algorithms: signal and model interaction
Artificial Intelligence in Medicine
Bayesian learning for cardiac SPECT image interpretation
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Knowledge discovery approach to automated cardiac SPECT diagnosis
Artificial Intelligence in Medicine
Paper: Multiple disorder diagnosis with adaptive competitive neural networks
Artificial Intelligence in Medicine
Probability density estimation from sampled data
IEEE Transactions on Information Theory
Credit card churn forecasting by logistic regression and decision tree
Expert Systems with Applications: An International Journal
A fuzzy approach to computer-assisted myocardial ischemia diagnosis
Artificial Intelligence in Medicine
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Logistic Regression by Means of Evolutionary Radial Basis Function Neural Networks
IEEE Transactions on Neural Networks
Uniformly Stable Backpropagation Algorithm to Train a Feedforward Neural Network
IEEE Transactions on Neural Networks
Improvements on Twin Support Vector Machines
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
A New Formulation for Feedforward Neural Networks
IEEE Transactions on Neural Networks
Noncircular Principal Component Analysis and Its Application to Model Selection
IEEE Transactions on Signal Processing
Review: Knowledge discovery in medicine: Current issue and future trend
Expert Systems with Applications: An International Journal
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This paper presents more accurate and reliable computational methods for aiding the treatment of people with coronary artery disease. New techniques are introduced for improved evaluation and distinguish cardiac disease affected patients from the healthy controls. Experiments are conducted with high level of error tolerance rate and confidence level at 95% and 99% and established the results with corrected T-tests based on comparison of various performance measures. Normal kernel density estimator is used for visual distinction of cardiac controls. A new ensemble learning method comprising of Bayesian network as classifier and Principal components method as the projection filter with ranker search is used for the relevant feature selection. Analysis of each model is performed and discusses major findings and concludes with promising results compared to the related works. Multiple Correspondence analysis is used for exploring heart disease variable's relationships. Robust machine learning algorithms used are Rotation forests, MultiBoosting, Sparse multinomial logistic regression for better performance with fine tuning of their involved parameters. The work aims at improving the software reliability and quality of diagnosis of cardiac disease with robust inference system. To the best of our knowledge, from the literature survey, experimental results presented in this work show best results with supportive statistical inference.