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Journal articles on the topic 'Artificial Intelligence in Psychiatry'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

MORICE, RODNEY. "Artificial Intelligence and Psychiatry." American Journal of Psychiatry 144, no. 10 (1987): 1352–53. http://dx.doi.org/10.1176/ajp.144.10.1352.

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SERVAN-SCHREIBER, DAVID. "Artificial Intelligence and Psychiatry." Journal of Nervous and Mental Disease 174, no. 4 (1986): 191–202. http://dx.doi.org/10.1097/00005053-198604000-00001.

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3

Alex, Neil S. "Artificial Intelligence and Psychiatry." JAMA: The Journal of the American Medical Association 255, no. 19 (1986): 2679. http://dx.doi.org/10.1001/jama.1986.03370190163046.

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Amanullah, Shabbir. "Artificial Intelligence in psychiatry." Archives of Biological Psychiatry 1 (November 20, 2023): 39–40. http://dx.doi.org/10.25259/abp_37_2023.

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5

Inamdar, Harshada Joshi. "Artificial Intelligence and Mental Health." International Journal of Nursing Research 10, no. 03 (2024): 29–31. http://dx.doi.org/10.31690/ijnr.2024.v010i03.007.

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In addition to identifying challenges and prospects for such application, this paper intends to present significant implementation science ideas that may be pertinent to comprehending and aiding artificial intelligence (AI) deployment in mental health care. This paper provides an overview of AI technology in modern mental health care and evaluates recent research developments, with a focus on the developing field of digital psychiatry. AI application in psychiatry to improve our knowledge, diagnosis, and treatment of mental diseases; to address concerns with availability, appeal, and accessibi

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Buckley, Patrick, Yanshan Wang, and Priya Gopalan. "Artificial Intelligence Scribes in Psychiatry." Focus 23, no. 1 (2025): 44–48. https://doi.org/10.1176/appi.focus.20240024.

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Lin, Eugene, Chieh-Hsin Lin, and Hsien-Yuan Lane. "Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches." International Journal of Molecular Sciences 21, no. 3 (2020): 969. http://dx.doi.org/10.3390/ijms21030969.

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A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with the accurate dose at the accurate time to patients with psychiatric disorders. In light of the latest advancements in artificial intelligence and machine learning techniques, numerous biomarkers and genetic loci associated with psychiatric diseases and relevant treatments are being discovered in precision psychiatry research by employing neuroimag

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Pham, Kay T., Amir Nabizadeh, and Salih Selek. "Artificial Intelligence and Chatbots in Psychiatry." Psychiatric Quarterly 93, no. 1 (2022): 249–53. http://dx.doi.org/10.1007/s11126-022-09973-8.

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Ray, Adwitiya, Akansha Bhardwaj, Yogender Kumar Malik, Shipra Singh, and Rajiv Gupta. "Artificial intelligence and Psychiatry: An overview." Asian Journal of Psychiatry 70 (April 2022): 103021. http://dx.doi.org/10.1016/j.ajp.2022.103021.

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Wyndowe, Jeffrey P. "Book Review: Artificial Intelligence and Psychiatry." Canadian Journal of Psychiatry 32, no. 7 (1987): 635. http://dx.doi.org/10.1177/070674378703200726.

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楊智傑, 楊智傑. "精神醫療再進化：結合人工智慧與精神醫學". 醫療品質雜誌 16, № 6 (2022): 068–75. http://dx.doi.org/10.53106/199457952022111606010.

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<p>精神疾病常被認為僅是心理問題，而忽略了大腦病理機轉的重要影響，造成精神醫學的診斷和評估仍停滯於主觀的症狀學診斷，而未能如內科疾病引入客觀的儀器診斷。近年來，越來越多的證據顯示精神疾病是大腦的問題。對於結構性和功能性磁振造影的解析，使得精神醫學有機會邁入生物標記診斷評估精神疾病的新階段。而機器學習方法的興起，對於大腦結構和功能數據的分析，更是帶來重要突破和深遠的影響。運用人工智慧與腦影像大數據，我們將有機會建立客觀評估精神疾病診斷與症狀嚴重程度的科學方法，除了能有效協助臨床醫師輔助評估精神疾病，提升精神醫療的照護品質，更重要的是能進一步解析大腦結構和功能與精神症狀的病理機轉，促進我們對於大腦此一人體最複雜的器官的理解，加速現代精神醫學的再進化。</p> <p>&nbsp;</p><p>Mental illness is occasionally dismissed as merely a psychological problem, with the underlying cause of brain pathology often ignored. This lack of knowledge has hindered the development of psychiatric diagnosis and

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Allen, Summer. "Artificial Intelligence and the Future of Psychiatry." IEEE Pulse 11, no. 3 (2020): 2–6. http://dx.doi.org/10.1109/mpuls.2020.2993657.

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Gerantia, M. "Artificial Intelligence in Psychiatry: A New Paradigm." European Psychiatry 67, S1 (2024): S205. http://dx.doi.org/10.1192/j.eurpsy.2024.442.

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IntroductionThe advent of artificial intelligence (AI) and machine learning has sparked interest in its applicability in the mental health domain, offering potential improvements in the efficiency and personalization of psychiatric services.ObjectivesTo characterize the methodological and technical approaches in studies utilizing machine learning and natural language processing (NLP) within mental health, to evaluate their potential and impact in psychiatric clinical practice, and to address the associated ethical concerns.MethodsA systematic review, adhering to the PRISMA guidelines, was cond

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Prathap, M. Sree. "The role of artificial intelligence in psychiatry." Indian Journal of Mental Health and Neurosciences 7, no. 2 (2024): 10–12. https://doi.org/10.54646/ijmhns.2024.08.

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Kerna, Nicholas A., Adina Boulos, Melany Abreu, et al. "Current Applications of Artificial Intelligence in Psychiatry." Scientia. Technology, Science and Society 2, no. 4 (2025): 125–43. https://doi.org/10.59324/stss.2025.2(4).10.

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The integration of artificial intelligence (AI) into psychiatric practice has accelerated rapidly, driven by advances in computational methods and the availability of diverse data sources. The present paper examines contemporary AI applications across diagnostic support, predictive analytics, therapeutic interventions, digital phenotyping, telepsychiatry integration, and ethical, legal, and social considerations. Foundations in machine learning, deep learning, and natural language processing are delineated alongside relevant data modalities, including structured clinical records, unstructured

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Rainey, Stephen, and Yasemin J. Erden. "Correcting the Brain? The Convergence of Neuroscience, Neurotechnology, Psychiatry, and Artificial Intelligence." Science and Engineering Ethics 26, no. 5 (2020): 2439–54. http://dx.doi.org/10.1007/s11948-020-00240-2.

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Abstract The incorporation of neural-based technologies into psychiatry offers novel means to use neural data in patient assessment and clinical diagnosis. However, an over-optimistic technologisation of neuroscientifically-informed psychiatry risks the conflation of technological and psychological norms. Neurotechnologies promise fast, efficient, broad psychiatric insights not readily available through conventional observation of patients. Recording and processing brain signals provides information from ‘beneath the skull’ that can be interpreted as an account of neural processing and that ca

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Janardan, Vipul, Manoj Kumar, and Prabhleen Singh. "The Transformative Role of Artificial Intelligence in Psychiatry: Enhancing Diagnosis and Treatment." Archives of Psychiatry 2, no. 1 (2024): 20–22. http://dx.doi.org/10.33696/psychiatry.2.009.

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This article delves into the groundbreaking applications of artificial intelligence (AI) in psychiatry, revolutionizing the field and improving patient care. AI technologies have shown immense potential in augmenting diagnostic accuracy, predicting treatment outcomes, and facilitating personalized therapeutic interventions. This article reviews the latest advancements and discusses the ethical considerations associated with AI integration in psychiatric practice.

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Andrić-Petrović, Sanja, and Nađa Marić. "Improvement of the psychiatric care through outsourcing artificial intelligence technologies: Where are we now?" Medicinska istrazivanja 55, no. 2 (2022): 19–29. http://dx.doi.org/10.5937/medi55-37718.

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Currently, the world is entering the fourth industrial revolution - marked by artificial intelligence (AI) powered technologies. The growing ubiquity of AI technologies is already present in many sectors of modern society, but caution still prevails in medicine where their application is far from routine, although it is on the constant rise. Psychiatry has been recognized as one of the disciplines where significant contribution of AI technologies is expected for prediction, diagnosis, treatment and monitoring of persons with psychiatric disorders. Nearly half of the world's population live in

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Baydili, İsmail, Burak Tasci, and Gülay Tasci. "Artificial Intelligence in Psychiatry: A Review of Biological and Behavioral Data Analyses." Diagnostics 15, no. 4 (2025): 434. https://doi.org/10.3390/diagnostics15040434.

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Artificial intelligence (AI) has emerged as a transformative force in psychiatry, improving diagnostic precision, treatment personalization, and early intervention through advanced data analysis techniques. This review explores recent advancements in AI applications within psychiatry, focusing on EEG and ECG data analysis, speech analysis, natural language processing (NLP), blood biomarker integration, and social media data utilization. EEG-based models have significantly enhanced the detection of disorders such as depression and schizophrenia through spectral and connectivity analyses. ECG-ba

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Gerantia, M. "Artificial Intelligence in Psychiatry: A Comprehensive Literature Review." European Psychiatry 67, S1 (2024): S61. http://dx.doi.org/10.1192/j.eurpsy.2024.173.

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IntroductionThe incorporation of artificial intelligence (AI) in healthcare, especially in mental health services, offers potential advancements in efficiency and personalization. As AI technologies like machine learning and natural language processing (NLP) continue to evolve, it’s vital to evaluate their applications in psychiatry comprehensively.ObjectivesThis review aims to summarize and characterize studies that used AI, particularly machine learning and NLP, in mental health. Additionally, it endeavors to understand how these technologies may enhance diagnostic tools, symptom monitoring,

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Kahambing, Jan Gresil. "ChatGPT, ‘polypsychic’ artificial intelligence, and psychiatry in museums." Asian Journal of Psychiatry 83 (May 2023): 103548. http://dx.doi.org/10.1016/j.ajp.2023.103548.

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Sun, Jie, Qun-Xi Dong, San-Wang Wang, et al. "Artificial intelligence in psychiatry research, diagnosis, and therapy." Asian Journal of Psychiatry 87 (September 2023): 103705. http://dx.doi.org/10.1016/j.ajp.2023.103705.

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23

Kelly, Brendan D. "Artificial Intelligence (AI) and academic publishing in psychiatry." International Journal of Law and Psychiatry 101 (July 2025): 102105. https://doi.org/10.1016/j.ijlp.2025.102105.

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24

Okpete, Uchenna Esther, and Haewon Byeon. "Challenges and prospects in bridging precision medicine and artificial intelligence in genomic psychiatric treatment." World Journal of Psychiatry 14, no. 8 (2024): 1148–64. http://dx.doi.org/10.5498/wjp.v14.i8.1148.

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Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical, genetic, environmental, and lifestyle factors to optimize medication management. This study investigates how artificial intelligence (AI) and machine learning (ML) can address key challenges in integrating pharmacogenomics (PGx) into psychiatric care. In this integration, AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions. AI-driven models integrating genomic, clinical, and demographic data demonstrated high accuracy in predi

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Shalini Verma, Shruti Sharma, and Dr. Pardeep Arora. "Mental Health Analysis with Artificial Intelligence." International Journal of Scientific Research in Science and Technology 12, no. 3 (2025): 992–1006. https://doi.org/10.32628/ijsrst25123109.

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This dissertation explores the role of AI technologies in modern mental healthcare and reviews recent developments achieved by researchers, with a special focus on the growing field of digital psychiatry. Furthermore, it delves into the ethical challenges associated with the expanding influence of artificial intelligence in mental healthcare. Mental health-related illnesses are considered one of the most significant global challenges, impacting millions of individuals worldwide and contributing to high rates of disability.Artificial intelligence is revolutionizing mental healthcare through its

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King, Morgan. "Harmful biases in artificial intelligence." Lancet Psychiatry 9, no. 11 (2022): e48. http://dx.doi.org/10.1016/s2215-0366(22)00312-1.

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27

Kudeikina, Inga, Marina Loseviča, and Nataliya O. Gutorova. "LEGAL AND PRACTICAL PROBLEMS OF USE OF ARTIFICIAL INTELLIGENCE-BASED ROBOTS IN FORENSIC PSYCHIATRY." Wiadomości Lekarskie 74, no. 11 (2021): 3042–47. http://dx.doi.org/10.36740/wlek202111231.

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The aim: This research aims to analyze the possibilities of using artificial intelligence-based robotics in forensic psychiatry to assess the public hazard of a mentally disabled or suffering from a mental illness to improve the legal framework governing the use of compulsory medical measures. Materials and methods: This study is based on the Republic of Latvia and Ukraine’s regulatory acts and the juridical practice of the Republic of Latvia. Dialectical, comparative, analytic, synthetic, system analyses, and sociological research methods were used. Conclusions: Different automated systems, i

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Simon, Gregory E., and Bobbi Jo Yarborough. "Good News: Artificial Intelligence in Psychiatry Is Actually Neither." Psychiatric Services 71, no. 3 (2020): 219–20. http://dx.doi.org/10.1176/appi.ps.201900464.

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Liu, Xin-Qiao, Xin-Yu Ji, Xing Weng, and Yi-Fan Zhang. "Artificial intelligence ecosystem for computational psychiatry: Ideas to practice." World Journal of Meta-Analysis 11, no. 4 (2023): 79–91. http://dx.doi.org/10.13105/wjma.v11.i4.79.

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Siddiqui, M. Aleem, and Shobit Garg. "Artificial intelligence and neuromodulation: A new frontier in psychiatry." Archives of Biological Psychiatry 2 (March 15, 2025): 55–56. https://doi.org/10.25259/abp_3_2025.

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Avula, *Vijaya Chandra Reddy, and Sridhar Amalakanti. "ARTIFICIAL INTELLIGENCE IN PSYCHIATRY, PRESENT TRENDS, AND CHALLENGES: AN UPDATED REVIEW." International Journal of Neuropsychopharmacology 28, Supplement_1 (2025): i213. https://doi.org/10.1093/ijnp/pyae059.373.

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Abstract Background Artificial intelligence (AI) is no longer just a figment of science fiction. Over the years, it has evolved into a tangible technology making significant strides in various industries, particularly in medicine. This fusion of advanced computer science and human-like problem-solving capabilities offers a unique perspective and a host of tools that can be harnessed to tackle intricate medical challenges, enhancing healthcare delivery. Aims & Objectives This review aims to elucidate the role and potential of AI in psychiatry, exploring its multifaceted advantages while cri

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Jeste, Dilip V., Sarah A. Graham, Tanya T. Nguyen, Colin A. Depp, Ellen E. Lee, and Ho-Cheol Kim. "Beyond artificial intelligence: exploring artificial wisdom." International Psychogeriatrics 32, no. 8 (2020): 993–1001. http://dx.doi.org/10.1017/s1041610220000927.

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ABSTRACTBackground:The ultimate goal of artificial intelligence (AI) is to develop technologies that are best able to serve humanity. This will require advancements that go beyond the basic components of general intelligence. The term “intelligence” does not best represent the technological needs of advancing society, because it is “wisdom”, rather than intelligence, that is associated with greater well-being, happiness, health, and perhaps even longevity of the individual and the society. Thus, the future need in technology is for artificial wisdom (AW).Methods:We examine the constructs of hu

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Agarwal, Khushboo. "Artificial Intelligence in the Management of Obesity." Indian Journal of Endocrinology and Metabolism 29, no. 3 (2025): 283–84. https://doi.org/10.4103/ijem.ijem_535_24.

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Abstract The prevalence of obesity has increased significantly in the last few years. Addressing obesity needs multifaceted strategy including prevention, accurate diagnosis, treatment of secondary causes, diet and exercise, behavioral changes and long term management. In addition it involves integration of multiple teams including endocrinologist, respiratory medicine, ENT, psychiatry, physiotherapy, diet, and bariatric surgeon. Artificial intelligence can help with each of these aspects by enabling predictive analysis, behavioral intervention in real time and improving patient outcome. There

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Li, Fei, Huaiqiang Sun, Bharat B. Biswal, John A. Sweeney, and Qiyong Gong. "Artificial intelligence applications in psychoradiology." Psychoradiology 1, no. 2 (2021): 94–107. http://dx.doi.org/10.1093/psyrad/kkab009.

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Abstract One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective treatments that target patient-relevant pathophysiological features. This is the primary aim of the field of Psychoradiology. Using databases collected from large samples at multiple centers, sophisticated artificial intelligence (AI) algorithms may be used to develop clinically useful imag

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Podoplelova, E. S. "ANALYSIS OF ARTIFICIAL INTELLIGENCE METHODS APPLIED TO SOLVING PSYCHIATRY PROBLEMS." IZVESTIYA SFedU. ENGINEERING SCIENCES, no. 2 (May 31, 2022): 180–89. http://dx.doi.org/10.18522/2311-3103-2022-2-180-189.

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Monteith, Scott, Tasha Glenn, John Geddes, Peter C. Whybrow, and Michael Bauer. "Commercial Use of Emotion Artificial Intelligence (AI): Implications for Psychiatry." Current Psychiatry Reports 24, no. 3 (2022): 203–11. http://dx.doi.org/10.1007/s11920-022-01330-7.

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Wong, Dustin. "74.3 Artificial Intelligence–Driven Psychiatry Interventions: From Chatbots to Toys." Journal of the American Academy of Child & Adolescent Psychiatry 63, no. 10 (2024): S103—S104. http://dx.doi.org/10.1016/j.jaac.2024.07.433.

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Lingewaran, Anand, and Pooja Govind Govind. "Artificial intelligence in psychiatry and mental health: A narrative review." IP Indian Journal of Neurosciences 11, no. 2 (2025): 76–81. https://doi.org/10.18231/j.ijn.2025.018.

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Eskandar, Kirolos. "Artificial intelligence in psychiatric diagnosis: challenges and opportunities in the era of machine learning." Debates em Psiquiatria 14 (September 17, 2024): 1–16. http://dx.doi.org/10.25118/2763-9037.2024.v14.1318.

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The integration of artificial intelligence (AI) into psychiatric diagnosis heralds a new era in mental health care, offering unprecedented opportunities to enhance diagnostic accuracy, personalize treatment, and streamline clinical workflows. A systematic approach was utilized, adhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. This literature review explores the current state of AI in psychiatric diagnosis, highlighting key technologies such as machine learning, natural language processing, and deep learning. We discuss the application of t

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Fawzy, Ahmad, Danastri Cantya Nirmala, Denaya Khansa, and Yudhistira Tri Wardhana. "Ethics and Regulation for Artificial Intelligence in Healthcare: Empowering Clinicians to Ensure Equitable and High-Quality Care." INTERNATIONAL JOURNAL OF MEDICAL SCIENCE AND CLINICAL RESEARCH STUDIES 03, no. 07 (2023): 1350–57. http://dx.doi.org/10.47191/ijmscrs/v3-i7-23.

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As artificial intelligence (AI) technology becomes increasingly integrated into healthcare, it is crucial for clinicians to possess a comprehensive understanding of its capabilities, limitations, and ethical implications. This literature review explores the reasons why clinicians need to be better informed about artificial intelligence, emphasizes the potential benefits of artificial intelligence in healthcare, raises awareness regarding the risks and unintended consequences associated with its use, discusses the development of machine learning and artificial intelligence in healthcare, and un

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Blease, C., C. Locher, M. Leon-Carlyle, and M. Doraiswamy. "Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey." DIGITAL HEALTH 6 (January 2020): 205520762096835. http://dx.doi.org/10.1177/2055207620968355.

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Background The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics. Objective This study aimed to explore psychiatrists’ opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice Methods In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descr

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Arendt, Florian, Benedikt Till, Martin Voracek, et al. "ChatGPT, Artificial Intelligence, and Suicide Prevention." Crisis 44, no. 5 (2023): 367–70. http://dx.doi.org/10.1027/0227-5910/a000915.

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Peeranna, Baburao. "ROLE OF ARTIFICIAL INTELLIGENCE IN ADVERTISEMENT." REVIEW JOURNAL PHILOSOPHY & SOCIAL SCIENCE 48, no. 2 (2023): 336–41. http://dx.doi.org/10.31995/rjpss.2023.v48i01.040.

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Tripathi, Raghvendra Narain. "Artificial Intelligence Solutions for the Disabled." Indian Journal of Computer Science 8, no. 6 (2023): 43. http://dx.doi.org/10.17010/ijcs/2023/v8/i6/173445.

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Ivliev, Grigoriy, and Mariya Egorova. "Legal Issues of the Legal Status of Artificial Intelligence and Products Created by Artificial Intelligence Systems." Journal of Russian Law 26, no. 6 (2023): 1. http://dx.doi.org/10.12737/jrl.2022.060.

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Welch, Victoria, Tom Joshua Wy, Anna Ligezka, et al. "Use of Mobile and Wearable Artificial Intelligence in Child and Adolescent Psychiatry: Scoping Review." Journal of Medical Internet Research 24, no. 3 (2022): e33560. http://dx.doi.org/10.2196/33560.

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Background Mental health disorders are a leading cause of medical disabilities across an individual’s lifespan. This burden is particularly substantial in children and adolescents because of challenges in diagnosis and the lack of precision medicine approaches. However, the widespread adoption of wearable devices (eg, smart watches) that are conducive for artificial intelligence applications to remotely diagnose and manage psychiatric disorders in children and adolescents is promising. Objective This study aims to conduct a scoping review to study, characterize, and identify areas of innovatio

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Erguzel, Turker, and Serhat Ozekes. "Artificial intelligence approaches in psychiatric disorders." Journal of Neurobehavioral Sciences 1, no. 2 (2014): 52. http://dx.doi.org/10.5455/jnbs.1405259279.

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Turan, Bahadır, Murat Gülşen, and Asım Egemen Yılmaz. "Artificial Intelligence Applications in Psychiatric Disorders." Journal of Ankara University Faculty of Medicine 75, no. 1 (2022): 56–62. http://dx.doi.org/10.4274/atfm.galenos.2022.36002.

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Rojas Malpica, Carlos, and Guillermo Cerceau. "Pensamiento, inteligencia artificial y medicina." Mente y Cultura 5, no. 1 (2024): 33–36. http://dx.doi.org/10.17711/myc.2683-3018.2024.003.

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Artificial intelligence (AI) is a technology that has revolutionized various fields of knowledge, including medicine. However, its use and potential in this area are not without controversies and misunderstandings. In this article, the authors, a computer scientist and a psychiatrist, critically analyze the concept of artificial intelligence and its applications in medicine, especially in psychiatry. To do this, they distinguish between intelligence and thought, and argue that the former is a tool of the latter, which is a much more complex and evolutionary mental faculty. Likewise, they quest

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Malgaroli, Matteo, and Katharina Schultebraucks. "Artificial Intelligence and Posttraumatic Stress Disorder (PTSD)." European Psychologist 25, no. 4 (2020): 272–82. http://dx.doi.org/10.1027/1016-9040/a000423.

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Abstract. Posttraumatic stress disorder (PTSD) is a debilitating disease that can occur after experiencing a traumatic event. Despite recent progress in computational research, it has not yet been possible to identify precise and reliable risk factors that enable predictive models of individual risk for posttraumatic stress after trauma. In this overview, we discuss recent advances in the use of Machine Learning (ML) and Artificial Intelligence (AI) for risk stratification and targeted treatment allocation in the context of stress pathologies and we critically review the benefits and challenge

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