Using machine learning to predict mental healthcare consumption in non-affective psychosis

Keyphrases

• Mental Health Care 100%
• Healthcare Consumption 100%
• Machine Learning 100%
• Non-affective Psychosis 100%
• Future Healthcare 36%
• Risk Factors 18%
• Service Users 9%
• Demand-driven 9%
• Patient Demographics 9%
• Model Risk 9%
• Machine Learning Techniques 9%
• Paid Employment 9%
• Predicting the Future 9%
• Health Consumer 9%
• Psychosis 9%
• Mental Health Systems 9%
• Healthcare Resources 9%
• Social Activity 9%
• Existing Data 9%
• Random Forest 9%
• Random Forest Method 9%
• Identifying Risk Factors 9%
• Identify Risk 9%
• Met Needs 9%
• Logistic Regression Classification 9%
• Psychotic Episode 9%
• Resource Allocation Optimization 9%
• Classification Tree 9%
• Prognostic Model 9%

Psychology

• Paid Employment 100%
• Prognostic Model 100%