Identification of clinical factors related to prediction of alcohol use disorder from electronic health records using feature selection methods

Computer Science

• Related Factor 100%
• Feature Selection 100%
• Random Decision Forest 30%
• Classification Performance 20%
• Feature Reduction 20%
• Feature Extraction 20%
• Operational Level 10%
• Support Vector Machine 10%
• Machine Learning Technique 10%
• Clinical Staff 10%
• Computational Problem 10%
• Filter Feature Selection 10%
• Machine Learning Algorithm 10%
• Ensemble Method 10%
• Medical Knowledge 10%
• Machine Learning 10%
• Learning System 10%

Biochemistry, Genetics and Molecular Biology

• Electronic Health Record 100%
• Feature Extraction 100%
• Random Forest 27%
• Support Vector Machine 9%
• K Nearest Neighbor 9%
• Digestive System 9%