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Applications of artificial intelligence technologies on mental health research during COVID-19

Author

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  • Hossain, Md Mahbub
  • McKyer, E. Lisako J.
  • Ma, Ping

Abstract

The coronavirus disease (COVID-19) pandemic has impacted mental health globally. It is essential to deploy advanced research methodologies that may use complex data to draw meaningful inferences facilitating mental health research and policymaking during this pandemic. Artificial intelligence (AI) technologies offer a wide range of opportunities to leverage advancements in data sciences in analyzing health records, behavioral data, social media contents, and outcomes data on mental health. Several studies have reported the use of several AI technologies such as vector machines, neural networks, latent Dirichlet allocation, decision trees, and clustering to detect and treat depression, schizophrenia, Alzheimer’s disease, and other mental health problems. The applications of such technologies in the context of COVID-19 is still under development, which calls for further deployment of AI technologies in mental health research in this pandemic using clinical and psychosocial data through technological partnerships and collaborations. Lastly, policy-level commitment and deployment of resources to facilitate the use of robust AI technologies for assessing and addressing mental health problems during the COVID-19 pandemic.

Suggested Citation

  • Hossain, Md Mahbub & McKyer, E. Lisako J. & Ma, Ping, 2020. "Applications of artificial intelligence technologies on mental health research during COVID-19," SocArXiv w6c9b, Center for Open Science.
    • Handle: RePEc:osf:socarx:w6c9b
    DOI: 10.31219/osf.io/w6c9b
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    Cited by:

    1. Aleksander Aristovnik & Dejan Ravšelj & Lan Umek, 2020. "A Bibliometric Analysis of COVID-19 across Science and Social Science Research Landscape," Sustainability, MDPI, vol. 12(21), pages 1-30, November.

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