Comparison of outcome prediction models post-stroke for a population-based registry with clinical variables collected at admission vs. discharge

Keyphrases

• Acute Setting 25%
• Age of Onset 25%
• Area under the Curve 50%
• At Discharge 50%
• Build Prediction 25%
• Clinical Data 25%
• Clinical Features 75%
• Clinical Variables 100%
• Curve-based 25%
• Discharge to Assess 25%
• Feature Selection 25%
• High Performance 25%
• Logistic Regression 50%
• National Institutes of Health Stroke Scale (NIHSS) 50%
• Outcome Prediction 100%
• Patient Subgroups 25%
• Population-based 25%
• Population-based Registry 100%
• Post-stroke 100%
• Prediction Model 25%
• Prognostic Outcome 25%
• Regression-based Method 25%
• Stroke Outcome 25%
• Stroke Patients 50%
• Stroke Registry 25%
• Taiwan Stroke Registry 25%
• Triage 50%

Medicine and Dentistry

• Apoplexy 100%
• Clinical Feature 50%
• Clinician 16%
• Feature Extraction 16%
• Logistic Regression Analysis 33%
• National Institutes of Health Stroke Scale 33%
• Onset Age 16%
• Prognosis 100%
• Triage 33%