Development and implementation of patient-level prediction models of end-stage renal disease for type 2 diabetes patients using fast healthcare interoperability resources

Nursing and Health Professions

• Prediction 100%
• Non Insulin Dependent Diabetes Mellitus 100%
• End Stage Renal Disease 100%
• Patient 100%
• Algorithm 66%
• Classifier 66%
• Electronic Medical Record System 66%
• Drug Therapy 33%
• Diabetes Mellitus 33%
• Logistic Regression Analysis 33%
• Insulin 33%
• Creatinine Blood Level 33%
• Charlson Comorbidity Index 33%
• Estimated Glomerular Filtration Rate 33%
• Albumin 33%
• Creatinine 33%
• Serum Albumin 33%
• Inpatient 33%
• Support Vector Machine 33%
• Patient with Type 2 Diabetes 33%
• Health Level 7 33%
• Random Forest 33%

Engineering

• Development 100%
• Health Care 100%
• Model Prediction 100%
• Stage Renal Disease 100%
• Models 66%
• Algorithm 66%
• Receivers 66%
• Electronic Medical Record 66%
• Characteristic Curve 66%
• Performance 33%
• Dataset 33%
• Support Vector Machine 33%
• Validation 33%
• Regression 33%
• Medical Data 33%
• Random Forest 33%
• Risk Prediction 33%

Computer Science

• Prediction Model 100%
• Interoperability 100%
• Machine Learning 100%
• Models 66%
• Algorithms 66%
• Classifier 66%
• Characteristic Curve 66%
• Electronic Medical Record 66%
• Logistic Regression 33%
• Support Vector Machine 33%
• Random Decision Forest 33%
• Server 33%
• Fold Cross Validation 33%
• Extreme Gradient Boosting 33%
• Unstructured Data 33%