Artificial Intelligence-driven and technological innovations in the diagnosis and management of substance use disorders.

Abstract

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.