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Updated: Sep 17, 2025

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
Published on: September 27, 2020
Machine Learning Insights for Adolescent Mental Health: A Data-Driven Approach for Functional Communication, Therapy,
Dafni Patsiala1, Anastasia Mantesi1, Magdalini Agrafioti1
1Ocelot Special Psychosocial Intervention Unit-f.C.T.E Society, Athens, Greece.
Abstract:
This study analyzes a sanitized cohort of 152 delinquency-referred adolescents (11-21 yrs; mean 16.3 ± 2.4) using two complementary, data-driven steps. First, we rank and plot the 20 most frequent ICD-10 codes, exposing a dominance of hyperkinetic (F90.x) and family-related psychosocial (Z63.5) diagnoses. Second, age and one-hot ICD flags feed a K-Means model whose four-cluster solution-visualised via t-SNE-delineates clinically coherent subgroups. The lightweight Python workflow shows how routinely collected records can swiftly surface high-risk profiles and guide targeted adolescent mental-health interventions.
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