London, June 23 (QNA) - Researchers in the United Kingdom and Germany have developed a new artificial intelligence model capable of advanced emotion analysis, potentially helping doctors diagnose mental health disorders with greater accuracy.

Researchers from the Universities of Nottingham and Kiel said that improving early and precise detection of mental health conditions could enable faster medical intervention before symptoms worsen.

Mental health disorders refer to a range of conditions affecting thinking, emotions, and behavior, including depression, anxiety, mood disorders, personality disorders, and schizophrenia, which can significantly impact daily functioning and social interaction.

The new model, named "Emo-MHC," is based on machine learning and deep learning techniques to analyze text from various sources such as clinical notes, social media posts, and online forums, enabling faster and more accurate classification of mental health conditions compared to existing systems.

Researchers noted that current models often rely on natural language processing and clinical self-assessments, which may lead to diagnostic errors or overlook emotional nuances. The new system operates in two stages: emotion extraction using advanced affect recognition techniques, followed by lexicon-based analysis to better interpret emotional context.

According to researchers, improved early diagnosis could enhance patient care, reduce pressure on healthcare systems, and ensure quicker access to appropriate treatment.

Dr. Sangeeta, a co-researcher from the University of Kiel, said rising rates of mental health disorders highlight the urgent need for effective early detection tools.

She added that artificial intelligence and large language models hold significant potential in supporting individuals facing mental health challenges, noting that improved diagnostic accuracy could save lives and reduce strain on healthcare services.

The research team plans to further refine the model and explore its practical application for broader use in mental health care. (QNA)