From Asylums to Algorithms: the Evolution of Psychiatry and the Emergence of AI and Biomarkers
Year: 2026
Type: article
Abstract: Psychiatry has undergone a profound transformation over the past two centuries, evolving from custodial models of care characterised by institutionalisation and limited therapeutic efficacy to a modern discipline grounded in evidence based, patient centred practice. Historically, people with mental illness were often confined to asylums where care prioritised containment over recovery. Invasive, poorly evidenced treatments were common, reflecting limited understanding of the biopsychosocial determinants of mental illness and contributing to stigma, loss of autonomy, and long-term harm. In response, contemporary psychiatry has adopted ethical safeguards, multidisciplinary approaches, and the biopsychosocial model, emphasising recovery oriented care, informed consent, and community integration. Alongside these conceptual shifts, advances in neuroscience and digital technology are driving a further paradigm change within the field. Artificial intelligence has gained increasing attention for its potential to enhance diagnostic accuracy, risk stratification, and treatment personalisation through the analysis of large and complex clinical datasets. Data driven computational methods are increasingly being applied to identify patterns that may support earlier diagnosis, improve prediction of treatment response, and enhance the efficiency and accessibility of mental health service delivery. In parallel, growing interest in biomarker informed psychiatry reflects efforts to address the historical absence of objective diagnostic tools within mental health care. Advances in genetics aim to improve diagnostic precision and treatment stratification, supporting more individualised and biologically informed care. This article examines the evolution of psychiatry from its historical foundations to emerging innovations in artificial intelligence and biomarkers that are shaping the future of precision mental health care.
Source: UCC Student Medical Journal
DOI: 10.33178/smj.2026.7
Institution: University College Cork
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7223674910