Deep Learning based Decision Support Framework for Cardiovascular Support Disease Prediction

Keyphrases

• Decision Support Framework 100%
• Deep Learning Methods 100%
• Class Imbalance 100%
• Disease Prediction 100%
• Cardiovascular Support 100%
• CNN Cascade 80%
• Dense CNN 80%
• Minority Class 60%
• National Health Interview Survey 60%
• NHANES 60%
• Survey Data 40%
• Machine Learning Models 40%
• Event Detection 40%
• Cascade Model 40%
• Deep Learning Model 40%
• CVD Events 40%
• Cascade Architecture 40%
• Class Distribution 40%
• Cardiovascular Disease 20%
• Model-driven Development 20%
• Publicly Available 20%
• Performance Improvement 20%
• Detection Task 20%
• Poor Performance 20%
• Resilient 20%
• Clinical Setting 20%
• Clinical Data 20%
• Detection Accuracy 20%
• Majority Class 20%
• Deep Learning 20%
• Specific Training 20%
• Control Class 20%
• Optimal Feature Selection 20%
• Class-specific 20%
• Learning Stages 20%
• Data Partitioning 20%
• Multiple Data 20%
• Feature Learning 20%
• Detection Performance 20%
• Cardiovascular Risk Prediction 20%
• Majority Voting 20%
• Training Routines 20%
• Traditional Machine Learning 20%
• Neural Network Cascade 20%
• Enhanced Detection 20%
• Partitioning Strategy 20%
• Homogenized Feature 20%
• Simulated Annealing Method 20%
• Least Absolute Shrinkage 20%
• Convolution Neural Network 20%
• Disease Class 20%

Computer Science

• Deep Learning Method 100%
• Convolutional Neural Network 100%
• Class Imbalance 100%
• Minority Class 60%
• Event Detection 40%
• Deep Learning Model 40%
• Class Distribution 40%
• Machine Learning Model 40%
• Model Development 20%
• Detection Accuracy 20%
• Majority Class 20%
• Clinical Setting 20%
• Clinical Data 20%
• Representation Learning 20%
• Majority Voting 20%
• Detection Performance 20%
• Simulated Annealing Approach 20%