AI’s Role in Identifying Anxiety in Youth through Brain Structure Analysis

AI revolutionizes healthcare by identifying anxiety disorders in youths aged 10 to 25 through brain structure analysis, says a study in Nature Mental Health.

By Sunil Sonkar 2 Min Read
2 Min Read
AI's Role in Identifying Anxiety in Youth through Brain Structure Analysis

Artificial intelligence (AI) is changing the game of technology at a rapid speed. Gradually it is becoming an important part of our lifestyle including studies, businesses and healthcare. Lately, it is learned that it can identify anxiety disorders in young people by just analyzing brain structure. A study published in the journal Nature Mental Health reveals the claim. The study involved around 3,500 youths aged between 10 and 25 from different parts of the world.

The research used a technique called machine learning (ML), which allows machines to learn from data without explicit programming. Researchers examined several factors such as cortical thickness, surface area and volumes of deep-lying brain regions as well.

Led by researcher Moji Aghajani, Assistant Professor at Leiden University in the Netherlands, the study believes that the latest approach could lead to a more personalized prevention, diagnosis and care for anxiety disorders as well.


Usually it is found that anxiety disorders starts at an early adulthood age and can cause significant emotional, social and economic challenges. Understanding the brain processes of the young people involved in these disorders has been limited until now due to the focus on average patients and not on individual differences.

Aghajani highlighted that traditional analytical techniques are not appropriate as these often fails to provide individual-level outcomes. With the integration of large and diverse datasets (big data) along with AI, the field is gradually shifting towards a more personalized approach.

The initial finding of the study is promising across various ethnicities, locations and clinical characteristics. Further refinement of algorithms and inclusion of additional brain data could enhance the accuracy of AI in this regard.

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