Classification and discrimination of emotion dysregulation disorders using machine learning

Key Points

• Classification algorithms effectively distinguish between different emotion dysregulation disorders, enhancing diagnostic accuracy.
• Key metrics indicate a high accuracy rate of 85% for the developed models in identifying emotional disorders.
• Machine learning techniques were employed, utilizing various data inputs to train classification models.
• Findings support the application of machine learning in psychiatric assessments, potentially transforming diagnosis.