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Personalizing Pain Care through AI-Based Risk Stratification: A Multidisciplinary Perspective

Personalizing Pain Care through AI-Based Risk Stratification: A Multidisciplinary Perspective
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Author(s): S. Ida Evangeline (Government College of Engineering, Tirunelveli, India)
Copyright: 2026
Pages: 20
Source title: Unveiling Technological Advancements and Interdisciplinary Solutions for Pain Care
Source Author(s)/Editor(s): Yiannis Koumpouros (Digital Innovation in Public Health Research Lab, University of West Attica, Greece)
DOI: 10.4018/979-8-3693-9501-1.ch004

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Abstract

Artificial intelligence (AI) is redefining how clinicians approach pain care by enabling the use of predictive analytics to identify risk patterns, personalize interventions, and support clinical decisions. This chapter explores the emerging role of AI-driven risk stratification in pain management, highlighting how machine learning models trained on diverse data—from electronic health records to wearable sensors—can forecast pain trajectories and treatment responses. We examine real-world applications in both acute and chronic pain settings, illustrating how AI tools are being integrated into clinical workflows and digital health platforms. The chapter also critically addresses ethical and regulatory challenges of AI in pain care beyond technical implementation. We discuss risks associated with algorithmic bias, data privacy, transparency, and patient autonomy, and provide insights into governance frameworks that facilitate safe and equitable deployment.

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