Incorporation of "Artificial Intelligence" for Objective Pain Assessment: A Comprehensive Review.

IF 4.1 2区 医学 Q1 CLINICAL NEUROLOGY Pain and Therapy Pub Date : 2024-06-01 Epub Date: 2024-03-02 DOI:10.1007/s40122-024-00584-8
Salah N El-Tallawy, Joseph V Pergolizzi, Ingrid Vasiliu-Feltes, Rania S Ahmed, JoAnn K LeQuang, Hamdy N El-Tallawy, Giustino Varrassi, Mohamed S Nagiub
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Abstract

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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结合 "人工智能 "进行客观疼痛评估:综合评述
疼痛是一个重要的健康问题,疼痛评估对于正确诊断、随访和有效管理疼痛至关重要。传统的疼痛评估方法往往存在主观性和可变性。主要问题是如何更好地了解人们是如何体验疼痛的。近年来,人工智能(AI)在改善临床诊断和决策方面发挥着越来越重要的作用。人工智能的应用为提高疼痛评估的准确性和效率提供了大有可为的机会。这篇综述文章概述了人工智能在疼痛评估方面的现状,并探讨了其在提高准确性、效率和个性化护理方面的潜力。通过研究现有文献、研究空白和未来方向,本文旨在为疼痛管理领域的进一步发展提供指导。我们通过多个网站进行了在线数据库搜索,以确定相关文章。纳入标准为2014年1月至2024年1月期间发表的英文文章。)全文临床试验、观察性研究、综述文章、系统综述和荟萃分析的文章均被纳入本综述。排除标准包括非英语文章、未提供免费全文的文章、涉及儿科患者的文章、病例报告和社论。本综述共纳入(47)篇文章。总之,将人工智能应用于疼痛管理可为疼痛评估提供有前景的解决方案。人工智能有可能提高客观疼痛评估的准确性、精确性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Pain and Therapy
Pain and Therapy CLINICAL NEUROLOGY-
CiteScore
6.60
自引率
5.00%
发文量
110
审稿时长
6 weeks
期刊介绍: Pain and Therapy is an international, open access, peer-reviewed, rapid publication journal dedicated to the publication of high-quality clinical (all phases), observational, real-world, and health outcomes research around the discovery, development, and use of pain therapies and pain-related devices. Studies relating to diagnosis, pharmacoeconomics, public health, quality of life, and patient care, management, and education are also encouraged. Areas of focus include, but are not limited to, acute pain, cancer pain, chronic pain, headache and migraine, neuropathic pain, opioids, palliative care and pain ethics, peri- and post-operative pain as well as rheumatic pain and fibromyalgia. The journal is of interest to a broad audience of pharmaceutical and healthcare professionals and publishes original research, reviews, case reports, trial protocols, short communications such as commentaries and editorials, and letters. The journal is read by a global audience and receives submissions from around the world. Pain and Therapy will consider all scientifically sound research be it positive, confirmatory or negative data. Submissions are welcomed whether they relate to an international and/or a country-specific audience, something that is crucially important when researchers are trying to target more specific patient populations. This inclusive approach allows the journal to assist in the dissemination of all scientifically and ethically sound research.
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