Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications.

Journal: Psychological medicine
PMID:

Abstract

Artificial intelligence (AI) has been recently applied to different mental health illnesses and healthcare domains. This systematic review presents the application of AI in mental health in the domains of diagnosis, monitoring, and intervention. A database search (CCTR, CINAHL, PsycINFO, PubMed, and Scopus) was conducted from inception to February 2024, and a total of 85 relevant studies were included according to preestablished inclusion criteria. The AI methods most frequently used were support vector machine and random forest for diagnosis, machine learning for monitoring, and AI chatbot for intervention. AI tools appeared to be accurate in detecting, classifying, and predicting the risk of mental health conditions as well as predicting treatment response and monitoring the ongoing prognosis of mental health disorders. Future directions should focus on developing more diverse and robust datasets and on enhancing the transparency and interpretability of AI models to improve clinical practice.

Authors

  • Pablo Cruz-Gonzalez
    Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore.
  • Aaron Wan-Jia He
    School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong.
  • Elly PoPo Lam
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Ingrid Man Ching Ng
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Mandy Wingman Li
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Rangchun Hou
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Jackie Ngai-Man Chan
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Yuvraj Sahni
    Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Nestor Vinas Guasch
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Tiev Miller
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Benson Wui-Man Lau
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
  • Dalinda Isabel Sánchez Vidaña
    Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.