Development and internal validation of machine learning-based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke

Keyphrases

• External Validation 100%
• Model Validation 100%
• Health Risk 100%
• Outcome Prediction 100%
• Internal Validation 100%
• Ischemic Stroke 100%
• Acute Ischemic Stroke 100%
• Development Validation 100%
• Risk Score 100%
• Machine Learning Models 100%
• Vascular Events 100%
• IScore 100%
• Random Forest 60%
• Support Vector Machine 60%
• XGBoost 60%
• Hospitalization 40%
• Composite Outcome 40%
• Three-machine 40%
• Statistical Model 20%
• Machine Learning 20%
• Statistical Methods 20%
• Comparative Analysis 20%
• Risk Prediction 20%
• Predictor Variables 20%
• Potential Predictors 20%
• All-cause Mortality 20%
• Scoring System 20%
• Clinical Usefulness 20%
• Machine Learning Based 20%
• Area under the Receiver Operating Characteristic (AUROC) 20%
• Recurrent Stroke 20%
• Extreme Gradient Boosting 20%
• Learning-based Predictive Model 20%

Mathematics

• Support Vector Machine 100%
• Predictor Variable 33%
• Statistical Method 33%
• Characteristic Curve 33%
• Predictive Model 33%
• Random Model 33%
• Scoring System 33%

Pharmacology, Toxicology and Pharmaceutical Science

• Brain Ischemia 100%
• All Cause Mortality 14%
• Cerebrovascular Accident 14%