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AI4TeenDep

Detection of depression in adolescents

AI4TeenDep is a machine learning-based solution designed to interpret data related to depression in adolescents. It uses executive function scales and speech recognition to identify patterns associated with depressive symptoms, facilitating earlier and more accurate assessment.

Problems to solve

The detection of depression in adolescents can be complex due to the variability in the presentation of symptoms and the lack of objective tools. This can delay diagnosis and treatment, severely affecting the mental health of young people. AI4TeenDep addresses this challenge by providing a technological tool that complements clinical assessment, improving accuracy and efficiency in case identification.

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Main features

  • Analysis of executive functions: Uses scientifically validated scales to assess key areas such as working memory, inhibitory control and planning.
  • Advanced voice recognition: Analyzes vocal patterns to identify characteristics associated with emotional states related to depression.
  • Machine learning models: Processes and correlates data to detect possible signs of depression with high accuracy.
  • Early detection: Identifies patterns associated with depressive symptoms before they worsen, allowing early intervention.
  • Complement for professionals: Provides psychologists and psychiatrists with objective and detailed information to support their evaluations.
  • Intuitive interface: Presents results in a clear and accessible format to facilitate interpretation by specialists.
  • Scalability: Capable of handling large volumes of data, adaptable to different clinical or school contexts.
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