Predicting mortality risk for preterm infants using random forest

Keyphrases

• Mortality Prediction 100%
• Mortality Risk 100%
• Preterm Infants 100%
• Random Forest 100%
• Random Forest Regression 100%
• Logistic Regression Model 66%
• Clinical Factors 66%
• Superior Performance 66%
• CRIB-II 66%
• At Birth 33%
• Clinical Data 33%
• Birth Weight 33%
• Hospital Course 33%
• Mortality Rate 33%
• Physiological Data 33%
• Gestational Age 33%
• Clinical Prediction Model 33%
• Aberrancy 33%
• Extremely Preterm Infants 33%
• Labeled Data 33%
• Capture Mortality 33%
• Very Preterm Birth 33%
• AUC Score 33%

Nursing and Health Professions

• Random Forest 100%
• Logistic Regression Analysis 50%
• Area under the Curve 50%
• Premature Labor 25%
• Gestational Age 25%
• Birth Weight 25%
• Mortality Rate 25%

Mathematics

• Logistic Regression Model 100%
• Retrospective Study 50%
• Gestational Age 50%