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Updated: Jan 10, 2026

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Published on: April 5, 2019

Artificial Intelligence, Informatics, and Pain in Aging.

Urszula A Snigurska¹, Ragnhildur I Bjarnadottir²

¹Pain Research and Intervention Center of Excellence, Clinical and Translational Science Institute, University of Florida, 2004 Mowry Road, PO Box 100242, Gainesville, FL 32610, USA.

Clinics in Geriatric Medicine

|November 21, 2025

Summary

Older adults face significant pain challenges in acute care. Artificial intelligence offers promising solutions for improving pain management in this population.

Keywords:

Aged Algorithms Artificial intelligence Clinical decision-making Evidence-based practice Large language models Pain management Precision medicine

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Published on: October 3, 2020

Area of Science:

Gerontology
Pain Medicine
Health Informatics

Background:

The aging population experiences a high prevalence of pain within acute care settings.
Pain management in older adults is complex and presents significant clinical challenges.
Current pain management strategies require enhancement to effectively address the needs of elderly patients.

Purpose of the Study:

To review recent advancements in artificial intelligence (AI).
To explore the potential of AI in improving pain management for older patients in acute care.
To identify how computational tools can address challenges in geriatric pain management.

Main Methods:

Literature review of recent advancements in artificial intelligence.
Analysis of computational tools and advanced analytics in pain management.
Synthesis of findings related to AI applications in acute care pain.

Main Results:

Artificial intelligence demonstrates significant potential for enhancing pain assessment and treatment.
Advanced analytics can provide personalized pain management strategies for older patients.
AI tools can help overcome complexities associated with pain in the aging population.

Conclusions:

AI advancements offer a promising avenue for improving pain management outcomes in acute care for the elderly.
Further research and implementation of AI are warranted to optimize geriatric pain care.
AI has the potential to revolutionize pain management by providing data-driven insights and personalized interventions.