Artificial intelligence and Psychiatry: An overview
- PMID: 35219978
- PMCID: PMC9760544
- DOI: 10.1016/j.ajp.2022.103021
Artificial intelligence and Psychiatry: An overview
Abstract
The burden of mental illness both in world and India is increasing at an alarming rate. Adding to it, there has been an increase in mental health challenges during covid-19 pandemic with a rise in suicide, loneliness and substance use. Artificial intelligence can act as a potential solution to address this shortage. The use of artificial intelligence is increasingly being employed in various fields of mental health like affective disorders, psychosis, and geriatric psychiatry. The benefits are various like lower costs, wider reach but at the same time it comes with its own disadvantages. This article reviews the current understanding of artificial intelligence, the types of Artificial intelligence, its current use in various mental health disorders, current status in India, advantages, disadvantages and future potentials. With the passage of time and digitalization of the modern age, there will be an increase in the use of artificial intelligence in psychiatry hence a detailed understanding will be thoughtful. For this, we searched PubMed, Google Scholar, and Science Direct, China national Knowledge Infrastructure (CNKI), Globus Index Medicus search engines by using keywords. Initial searches involved the use of each individual keyword while the later searches involved the use of more than one word in different permutation combinations.
Keywords: Artificial Intelligence; Artificial Wisdom; Burden of mental illness; Psychiatry.
Copyright © 2022 Elsevier B.V. All rights reserved.
Conflict of interest statement
None declared.
References
-
- Afifi, A., Nakaguchi, T., 2015. Unsupervised detection of liver lesions in CT images, in: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2015, 2411–2414. - PubMed
-
- Antonucci L.A., Raio A., Pergola G., Gelao B., Papalino M., Rampino A., Andriola I., Blasi G., Bertolino A. Machine learning-based ability to classify psychosis and early stages of disease through parenting and attachment-related variables is associated with social cognition. BMC Psychol. 2021;9(1):47. - PMC - PubMed
-
- Appaji A., Nagendra B., Chako D.M., Padmanabha A., Jacob A., Hiremath C.V., Varambally S., Kesavan M., Venkatasubramanian G., Rao S.V., Webers C.A.B., Berendschot T.T.J.M., Rao N.P. Examination of retinal vascular trajectory in schizophrenia and bipolar disorder. Psychiatry Clin. Neurosci. 2019;73(12):738–744. - PubMed
-
- Ashburn T.T., Thor K.B. Drug repositioning: identifying and developing new uses for existing drugs. Nat. Rev. Drug Discov. 2004;3(8):673–683. - PubMed
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