A comparative analysis of methods for predicting clinical outcomes using high-dimensional genomic datasets.

Keyphrases

• Clinical Outcome Prediction 100%
• Comparative Analysis 100%
• Multivariate Classifier 100%
• Genomic Datasets 100%
• Method Analysis 100%
• Naïve Bayes 71%
• Bayesian Network 57%
• Network-based Methods 57%
• Single nucleotide Polymorphism 42%
• Genome-wide Association Study 28%
• Logistic Regression 28%
• Epistatic Interactions 28%
• Least Absolute Shrinkage and Selection Operator (LASSO) 28%
• Regression Support Vector Machine 28%
• Extreme Learning Machine 28%
• Binary Prediction 28%
• Outcome Prediction 14%
• Strong Predictor 14%
• Prediction Method 14%
• Predicting Diseases 14%
• Binary Outcome 14%
• Weak Predictors 14%
• Disease Status 14%
• Support Vector Machine 14%
• Feature Selection 14%
• Epistasis 14%
• Semi-synthetic 14%
• Overfitting 14%
• Simulated Dataset 14%
• Naive Bayes Model 14%
• Prediction Skill 14%
• Sample Testing 14%
• Cross-validation Study 14%
• 5-fold Cross Validation 14%
• Support Vector Machine Learning 14%
• High-dimensional Genomic Data 14%
• Bayes Model Averaging 14%

Computer Science

• Bayesian Networks 100%
• Clinical Outcome 100%
• Comparative Analysis 100%
• Support Vector Machine 75%
• Wide Association Study 50%
• Extreme Learning Machine 50%
• Logistic Regression 50%
• Dimensional Discrete 50%
• Feature Selection 25%
• Naïve Bayes Model 25%
• Feature Extraction 25%

Mathematics

• Bayesian 100%
• Naïve Bayes 85%
• Bayesian Network 57%
• Support Vector Machine 42%
• Logistic Regression 28%
• Prediction Method 28%
• Cross-Validation 14%
• Method Performs 14%
• Validation Study 14%
• Disease Status 14%