Towards artificial intelligence application in pain medicine

Abstract

Pain is a complex, multidimensional experience involving significant challenges in both diagnosis and management. While acute pain serves as a critical warning mechanism, chronic pain encompasses intricate biological, psychological, and social components, complicating its assessment and treatment. Artificial intelligence (AI) technologies are revolutionizing medicine and healthcare. Here we present an overview of the recent advances in AI for pain medicine. For example, the emergence of automatic pain assessment (APA) methodologies offers promising avenues for more objective pain evaluation. For APA aims, AI technologies, including machine learning algorithms and deep learning architectures such as natural language processing systems, have shown potential in analyzing biosignals, facial expressions, and speech patterns related to pain. However, the integration of these objective measures with traditional self-reporting remains essential for a comprehensive approach to pain diagnosis. Notably, APA models can be implemented for pain diagnosis in newborn and non-communicative patients. Additionally, the application of AI extends beyond pain diagnosis to personalized treatment strategies, predict opioid use disorders, education and training, clinical trajectory definition, and telehealth and real-time. Despite the potential of these innovations, challenges such as validation, parameter selection, and ethical aspects of technical implementation must be addressed.