Artificial Intelligence in Psychiatry: Opportunities, Challenges, and Future Directions.
Background: Mental disorders are a major contributor to the global burden of disease, highlighting the urgent need for more effective, accessible, and personalized psychiatric care. In parallel, rapid development of digital technologies has accelerated the integration of artificial intelligence (AI)...
| Published in: | International Medical Journal Vol. 33; no. 2; pp. 140 - 144 |
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| Main Authors: | , , , , , , |
| Format: | review Journal Article |
| Published: |
Japan International Cultural Exchange Foundation
Jun2026
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194702686&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194702686 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13412051 23J1 jtl: International Medical Journal issn: 13412051 maglogo: N pubinfo: dt: Jun2026 vid: 33 iid: 2 pid: 29386 pub: Japan International Cultural Exchange Foundation artinfo: ui: 194702686 194702686 194702686 194702686 ppf: 140 ppct: 4 formats: fmt: @attributes: type: P tig: atl: Artificial Intelligence in Psychiatry: Opportunities, Challenges, and Future Directions. aug: au: Sygacz, Maja Patryn, Rafał Januszczak, Radosław Bojarska, Wiktoria Cholewa, Julianna Białek, Agnieszka Barbara Gilarska, Gabriela Anna affil: The Medical and Pharmaceutical Law Laboratory, Medical University of Lublin, 7 Chodźki St, 20-093 Lublin, Poland sug: subj: Artificial Intelligence Utilization Psychiatry Manuscripts Research, Medical Health Knowledge Mental Health Services Digital Health Mental Disorders Diagnosis Mental Disorders Therapy Prediction Models Smartphone Wearable Sensors Magnetic Resonance Imaging Electronic Health Records Patient-Reported Outcomes Pedigree Neuroradiography Global Burden of Disease Psychiatric Care Health Services Accessibility Medical Informatics Privacy and Confidentiality Multidisciplinary Care Team Collaboration Machine Learning Deep Learning Natural Language Processing ab: Background: Mental disorders are a major contributor to the global burden of disease, highlighting the urgent need for more effective, accessible, and personalized psychiatric care. In parallel, rapid development of digital technologies has accelerated the integration of artificial intelligence (AI) into medicine. Objective: The objective of this manuscript is to provide an overview of current state of knowledge regarding AI applications in psychiatry, with the emphasis on associated limitations, challenges and directions for future research. Material and Methods: This review was based on scientific publications retrieved from PubMed and Google Scholar databases which were then subjected into a comprehensive review. Results: Potential benefits of AI include improved diagnostic accuracy, earlier detection of mental disorders, enhanced treatment personalization, and increased accessibility of psychiatric services. However, despite promising developments, AI implementation into psychiatry raises significant challenges. Key limitations include issues related to data quality, algorithmic bias, lack of transparency, and limited generalizability of models across diverse populations. Ethical and legal concerns, such as patient privacy, informed consent, and responsibility for clinical decisions, remain critical barriers to widespread implementation. Conclusions: AI holds substantial promise for transforming psychiatric care, but its safe and effective integration requires rigorous validation, ethical oversight, and interdisciplinary collaboration. pubtype: Academic Journal doctype: review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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