Medical & Clinical Research

Author(s): Bahman Zohuri

Intermittent Explosive Disorder (IED) is a psychiatric condition characterized by sudden, repeated episodes of impulsive aggression and disproportionate angry outbursts. Classified under Impulse-Control Disorders (ICDs) in the DSM-5, IED involves a failure to manage aggressive impulses, often resulting in verbal tirades or physical altercations. This condition is frequently misunderstood or misdiagnosed, especially in children and adolescents, where its symptoms may overlap with other behavioral disorders such as Oppositional Defiant Disorder (ODD). While ODD is marked by a persistent pattern of defiant and hostile behavior toward authority figures, it rarely escalates to the physical aggression seen in IED. Understanding the distinctions and relationships among IED, ICDs, and ODD is crucial for accurate diagnosis, early intervention, and effective treatment. This article explores the characteristics of IED, its connection to related disorders, and the importance of differentiating between them to ensure targeted clinical care and improved mental health outcomes. The integration of Artificial Intelligence (AI) and Machine Learning (ML) is transforming the landscape of mental health care, particularly for disorders like Intermittent Explosive Disorder (IED). By analyzing behavioral patterns, physiological data, and emotional cues, AI can help detect early warning signs of IED before major outbursts occur. Moreover, machine learning models can personalize treatment strategies, optimize therapy sessions, and provide real-time emotional support through digital platforms-paving the way for more proactive and precise mental health interventions.