Neurocognitive predictors of adherence to an online pain self-management program adjunct to long-term opioid therapy

Fleck, David E.; Wilson, Marian; Lewis, Daniel; Welge, Jeffrey A.; Arya, Grace; Sathyan, Anoop; Cohen, Kelly; Winhusen, T. John

doi:10.1080/13803395.2023.2221396

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Ai-based Pain Management1

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2024

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“…AI’s predictive capabilities have proved instrumental in determining a patient’s response to different pain management interventions. Fleck et al ( 54 ) examines neurocognitive predictors of adherence to an online pain self-management program for individuals undergoing long-term opioid therapy. The key findings indicate that selective attention and response inhibition/speed are significant predictors of program engagement.…”

Section: Ai-based Pain Managementmentioning

confidence: 99%

Transforming medicine: artificial intelligence integration in the peripheral nervous system

Qian,

Alhaskawi,

Dong

et al. 2024

Front. Neurol.

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In recent years, artificial intelligence (AI) has undergone remarkable advancements, exerting a significant influence across a multitude of fields. One area that has particularly garnered attention and witnessed substantial progress is its integration into the realm of the nervous system. This article provides a comprehensive examination of AI’s applications within the peripheral nervous system, with a specific focus on AI-enhanced diagnostics for peripheral nervous system disorders, AI-driven pain management, advancements in neuroprosthetics, and the development of neural network models. By illuminating these facets, we unveil the burgeoning opportunities for revolutionary medical interventions and the enhancement of human capabilities, thus paving the way for a future in which AI becomes an integral component of our nervous system’s interface.

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Section: Ai-based Pain Managementmentioning

confidence: 99%