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Related Experiment Video

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High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity
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AI in mental health.

Simon D'Alfonso1

  • 1The University of Melbourne School of Computing and Information Systems, Australia.

Current Opinion in Psychology
|July 1, 2020
PubMed
Summary

Artificial intelligence (AI) and machine learning are revolutionizing mental healthcare by enabling personalized digital treatments and early detection of conditions. Analyzing digital exhaust and language patterns offers new insights for prediction and intervention.

Area of Science:

  • Digital mental health
  • Artificial intelligence in healthcare
  • Machine learning applications

Background:

  • Digital approaches are transforming mental healthcare delivery.
  • Artificial intelligence (AI), particularly machine learning, is increasingly integral to developing mental health solutions.
  • Abundant data streams, including 'digital exhaust' from personal devices and social media, offer novel insights.

Purpose of the Study:

  • To explore the role of AI and machine learning in mental healthcare.
  • To highlight AI's application in personalized digital interventions and mental health prediction/detection.
  • To examine the use of natural language processing (NLP) for inferring mental health and therapeutic applications.

Main Methods:

  • Leveraging AI and machine learning for data-driven prediction and detection models.

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  • Analyzing 'digital exhaust' – data from personal digital devices and social media interactions.
  • Utilizing natural language processing (NLP) to quantitatively analyze language for mental health insights.

    • Main Results:

    • AI enhances digital interventions like web and smartphone apps for personalized mental healthcare.
    • AI-driven models can predict and detect mental health conditions using large datasets.
    • NLP provides a quantitative method for inferring mental health status from language.

    Conclusions:

    • AI and machine learning are powerful tools for advancing mental healthcare prediction, detection, and treatment.
    • Digital exhaust and NLP represent significant data sources for understanding and addressing mental health.
    • AI facilitates personalized digital interventions and the development of therapeutic conversational agents.