ClusteredSHAP: Faster GradientExplainer based on K-means Clustering and Selections of Gradients in Explaining 12-Lead ECG Classification Model

Keyphrases

• Classification Model 100%
• K-means 100%
• Deep Learning 100%
• 12-lead Electrocardiogram 100%
• Usability Score 100%
• Electrocardiogram Classification 100%
• Patient Care 50%
• Clinical Practice 50%
• Warning Signs 50%
• Neural Network 50%
• Computational Efficiency 50%
• Efficient Detection 50%
• Black Box 50%
• Time Application 50%
• User Experience 50%
• High Magnitude 50%
• Medical Setting 50%
• Common Knowledge 50%
• Health Systems 50%
• Medical Diagnostics 50%
• Medical Devices 50%
• Computational Demand 50%
• Complex Decisions 50%
• Cardiac Anomalies 50%
• Precise Detection 50%
• XAI Technique 50%
• SHAP Method 50%
• Tool Usability 50%
• Electrocardiogram Signals Classification 50%
• Blunders 50%
• Explainable AI 50%
• Usability Standards 50%
• Medical Scenarios 50%

Computer Science

• Classification Models 100%
• K-Means Clustering 100%
• Explainable Artificial Intelligence 100%
• Usability Score 66%
• Deep Learning Method 66%
• Neural Network 33%
• Computational Efficiency 33%
• User Experience 33%
• Direct Implementation 33%
• Real-Time Application 33%
• Common Knowledge 33%
• Gradient Magnitude 33%
• Computer Aided Manufacturing 33%