Implementing PainChek and PARO to Support Pain Assessment and Management in Residents with Dementia: A Qualitative Study

Pu, Lihui; Coppieters, Michel W.; Smalbrugge, Martin; Jones, Cindy; Byrnes, Joshua; Todorovic, Michael; Moyle, Wendy

doi:10.1016/j.pmn.2023.04.001

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2024

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Experience and Acceptance of AI, Expert Systems and Robots in Medical Fields

Freudenberg,

Brück,

Eiler

2024

IFMBE Proceedings

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Experience and Acceptance of AI, Expert Systems and Robots in Medical Fields

Freudenberg,

Brück,

Eiler

2024

IFMBE Proceedings

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Incorporation of “Artificial Intelligence” for Objective Pain Assessment: A Comprehensive Review

El-Tallawy,

Pergolizzi,

Vasiliu-Feltes

et al. 2024

Pain Ther

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Pain is a significant health issue, and pain assessment is essential for proper diagnosis, follow-up, and effective management of pain. The conventional methods of pain assessment often suffer from subjectivity and variability. The main issue is to understand better how people experience pain. In recent years, artificial intelligence (AI) has been playing a growing role in improving clinical diagnosis and decision-making. The application of AI offers promising opportunities to improve the accuracy and efficiency of pain assessment. This review article provides an overview of the current state of AI in pain assessment and explores its potential for improving accuracy, efficiency, and personalized care. By examining the existing literature, research gaps, and future directions, this article aims to guide further advancements in the field of pain management. An online database search was conducted via multiple websites to identify the relevant articles. The inclusion criteria were English articles published between January 2014 and January 2024). Articles that were available as full text clinical trials, observational studies, review articles, systemic reviews, and meta-analyses were included in this review. The exclusion criteria were articles that were not in the English language, not available as free full text, those involving pediatric patients, case reports, and editorials. A total of (47) articles were included in this review. In conclusion, the application of AI in pain management could present promising solutions for pain assessment. AI can potentially increase the accuracy, precision, and efficiency of objective pain assessment.

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