Computer-Assisted Clinical Diagnosis and Treatment

Hamid, Naveed S.; Portnoy, Jay M.; Pandya, Aarti

doi:10.1007/s11882-023-01097-8

Cited by 5 publications

(1 citation statement)

References 42 publications

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“… 6 , 7 In addition, AI’s applications in pain management education include simplifying complex pain mechanisms, offering evidence-based treatment recommendations, and supporting adherence through personalized reminders and reinforcement. 8 , 9 However, ethical considerations, patient empowerment, and accessibility barriers must be addressed for the successful integration of AI in patient education. Future advancements may involve natural language processing (NLP) and machine learning (ML) to further enhance customization and collaboration among healthcare professionals, AI experts, and educators to optimize pain management outcomes and patient satisfaction.…”

Section: Introductionmentioning

confidence: 99%

Reviewing the Potential Role of Artificial Intelligence in Delivering Personalized and Interactive Pain Medicine Education for Chronic Pain Patients

Robinson,

D'Souza,

Yazdi

et al. 2024

JPR

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The integration of artificial intelligence (AI) in patient pain medicine education has the potential to revolutionize pain management. By harnessing the power of AI, patient education becomes more personalized, interactive, and supportive, empowering patients to understand their pain, make informed decisions, and actively participate in their pain management journey. AI tailors the educational content to individual patients’ needs, providing personalized recommendations. It introduces interactive elements through chatbots and virtual assistants, enhancing engagement and motivation. AI-powered platforms improve accessibility by providing easy access to educational resources and adapting content to diverse patient populations. Future AI applications in pain management include explaining pain mechanisms, treatment options, predicting outcomes based on individualized patient-specific factors, and supporting monitoring and adherence. Though the literature on AI in pain medicine and its applications are scarce yet growing, we propose avenues where AI may be applied and review the potential applications of AI in pain management education. Additionally, we address ethical considerations, patient empowerment, and accessibility barriers.

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