Disorder-specific versus transdiagnostic cognitive mechanisms in anxiety and depression: Machine-learning-based prediction of symptom severity

Keyphrases

• Depressive Symptoms 100%
• Anxiety Symptoms 100%
• Psychiatric Assessment 100%
• Symptom Severity 100%
• Transdiagnostic 100%
• Disorder-specific 100%
• Cognitive Mechanisms 100%
• Machine Learning Prediction 100%
• Behavioral Tests 50%
• Depression Level 50%
• Expectancy 50%
• Anxiety Level 50%
• Cognitive Behavior 50%
• Memory Control 50%
• Cognitive Control 50%
• Selective Attention 50%
• Attention Control 50%
• Spatial Attention 50%
• Overfitting 50%
• Mechanism-based 50%
• Research Domain Criteria (RDoC) 50%
• Beck Depression inventory-II (BDI-II) 50%
• Internal Validation 50%
• Spatial Memory 50%
• Expectancy Bias 50%
• Cognitive Bias 50%
• Interpretation Bias 50%
• Success Rate 50%
• Two-view 50%
• Self-reported Symptoms 50%
• Anxious-depressed 50%
• Method Validation 50%
• Transdiagnostic Approach 50%
• Individual Bias 50%
• Cognitive Patterns 50%
• STAI-T 50%
• Intermediate Approach 50%
• Discrete Disorder 50%
• Spatial Cognitive 50%
• Novel Intermediate 50%
• Random Forest Regressor 50%
• Dimensional Diagnosis 50%
• Size Limit 50%

Psychology

• Behavioral Test 100%
• Cognitive Bias 100%
• Executive Function 100%