Tassinari Daniela Lé, Pozzolo Pedro Maria Olivia, Pozzolo Pedro Manoela, Negrão André Brooking, Abrantes do Amaral Ricardo, Malbergier André, Crispim Douglas Henrique, Castaldelli-Maia João Maurício
Instituto Perdizes (IPER), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, São Paulo, SP, Brazil.
Department of Psychiatry, Medical School, University of São Paulo, São Paulo, Brazil.
Int Rev Psychiatry. 2025 Feb;37(1):52-58. doi: 10.1080/09540261.2024.2432369. Epub 2024 Dec 2.
Substance Use Disorders (SUD) lead to a collection of health challenges such as overdoses and clinical diseases. Populations that are vulnerable and lack straightforward treatment access are vulnerable to significant economic and social effects linked to SUD. The ongoing advances in technology, especially Artificial Intelligence (AI), promise new ways to reduce the effects of SUD, refine treatment standards, and minimize the risk of relapse through tailored treatment plans. Recent innovations in functional neuroimaging techniques, such as fMRI, have led to the ability to detect brain patterns associated with drug use, and biomarkers in blood testing provide crucial diagnostic support. In addition, digital platforms applied for behavioral assessment supported by AI and natural language processing improve the early recognition of substance consumption trends, allowing for targeted interventions reliant on real-time data. Using pharmacogenetics and resources like mobile apps and wearable devices makes the development of care programs that continuously track substance use, mental health, and physical changes possible. At the core of ethical issues related to the application of AI for SUD are the rights of patients to have their privacy protected to ensure that all people justly have access to these technologies. The advancement of AI models provides significant possibilities to support clinical judgment and enhance patient outcomes.
物质使用障碍（SUD）会引发一系列健康挑战，如药物过量和临床疾病。弱势群体以及缺乏直接治疗途径的人群容易受到与SUD相关的重大经济和社会影响。技术的不断进步，尤其是人工智能（AI），有望带来新的方法来减轻SUD的影响、完善治疗标准，并通过量身定制的治疗计划将复发风险降至最低。功能神经成像技术（如功能磁共振成像）的最新创新使得能够检测与药物使用相关的脑模式，而血液检测中的生物标志物提供了关键的诊断支持。此外，由人工智能和自然语言处理支持的用于行为评估的数字平台改善了对物质消费趋势的早期识别，从而实现基于实时数据的有针对性干预。利用药物遗传学以及移动应用程序和可穿戴设备等资源，使得开发能够持续跟踪物质使用、心理健康和身体变化的护理计划成为可能。与将人工智能应用于SUD相关的伦理问题的核心是患者享有隐私保护的权利，以确保所有人都能公平地使用这些技术。人工智能模型的进步为支持临床判断和改善患者预后提供了重大可能性。
