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Current Psychiatry Reports

, 21:116 | Cite as

Artificial Intelligence for Mental Health and Mental Illnesses: an Overview

  • Sarah Graham
  • Colin Depp
  • Ellen E. Lee
  • Camille Nebeker
  • Xin Tu
  • Ho-Cheol Kim
  • Dilip V. JesteEmail author
Psychiatry in the Digital Age (J Shore, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Psychiatry in the Digital Age

Abstract

Purpose of Review

Artificial intelligence (AI) technology holds both great promise to transform mental healthcare and potential pitfalls. This article provides an overview of AI and current applications in healthcare, a review of recent original research on AI specific to mental health, and a discussion of how AI can supplement clinical practice while considering its current limitations, areas needing additional research, and ethical implications regarding AI technology.

Recent Findings

We reviewed 28 studies of AI and mental health that used electronic health records (EHRs), mood rating scales, brain imaging data, novel monitoring systems (e.g., smartphone, video), and social media platforms to predict, classify, or subgroup mental health illnesses including depression, schizophrenia or other psychiatric illnesses, and suicide ideation and attempts. Collectively, these studies revealed high accuracies and provided excellent examples of AI’s potential in mental healthcare, but most should be considered early proof-of-concept works demonstrating the potential of using machine learning (ML) algorithms to address mental health questions, and which types of algorithms yield the best performance.

Summary

As AI techniques continue to be refined and improved, it will be possible to help mental health practitioners re-define mental illnesses more objectively than currently done in the DSM-5, identify these illnesses at an earlier or prodromal stage when interventions may be more effective, and personalize treatments based on an individual’s unique characteristics. However, caution is necessary in order to avoid over-interpreting preliminary results, and more work is required to bridge the gap between AI in mental health research and clinical care.

Keywords

Technology Machine learning Natural language processing Deep learning Schizophrenia Depression Suicide Bioethics Research ethics 

Notes

Funding Information

This study was supported, in part, by the National Institute of Mental Health T32 Geriatric Mental Health Program (grant MH019934 to DVJ [PI]), the IBM Research AI through the AI Horizons Network IBM-UCSD AI for Healthy Living (AIHL) Center, by the Stein Institute for Research on Aging at the University of California San Diego, and by the National Institutes of Health, Grant UL1TR001442 of CTSA funding. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Compliance with Ethical Standards

Conflict of Interest

Sarah Graham, Xin Tu, and Ho-Cheol Kim each declare no potential conflicts of interest.

Colin Depp and Dilip V. Jeste are Co-Directors of UCSD-IBM Center on Artificial Intelligence for Healthy Living (2018–2022). This is a grant to UCSD from IBM. Drs. Depp and Jeste have no commercial interest in IBM or any other AI-related companies.

Ellen E. Lee has received grants from The National Institute of Mental Health, The National Institutes of Health, and The Stein Institute for Research on Aging.

Camille Nebeker is a co-investigator on a grant supported by IBM and her research on the ethics of emerging technologies is supported by the Robert Wood Johnson Foundation.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Sarah Graham
    • 1
    • 2
  • Colin Depp
    • 1
    • 2
    • 3
  • Ellen E. Lee
    • 1
    • 2
    • 3
  • Camille Nebeker
    • 4
  • Xin Tu
    • 1
    • 2
  • Ho-Cheol Kim
    • 5
  • Dilip V. Jeste
    • 1
    • 2
    • 6
    • 7
    Email author
  1. 1.Department of PsychiatryUniversity of California San DiegoLa JollaUSA
  2. 2.Sam and Rose Stein Institute for Research on AgingUniversity of California La JollaLa JollaUSA
  3. 3.VA San Diego Healthcare SystemSan DiegoUSA
  4. 4.Department of Family Medicine and Public HealthUniversity of California La JollaLa JollaUSA
  5. 5.Scalable Knowledge IntelligenceIBM Research-AlmadenSan JoseUSA
  6. 6.Department of NeurosciencesUniversity of California La JollaLa JollaUSA
  7. 7.University of California San DiegoLa JollaUSA

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