利用人工智能诊断、评估和管理慢性疼痛。

Q3 Medicine
Habib Zakeri, Mohammad Radmehr, Farnaz Khademi, Pegah Pedramfard, Leala Montazeri, Mahshid Ghanaatpisheh, Behnam Rahnama, Parisa Mahdiyar, Saba Moalemi, Farnaz Hemati, Aliasghar Karimi
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引用次数: 0

摘要

慢性疼痛是一种普遍的疾病,也是全世界旷工的主要原因。这种情况包括持续三个月以上的持续疼痛,严重影响患者的生活质量和社会交往。虽然慢性疼痛的原因往往是未知的,但对于各种已知的原因,没有明确的治疗方法。此外,疼痛的评估和预测可能具有挑战性,特别是在重症监护病房接受护理的无意识患者。通常采用主观测量和传统方法进行诊断、评估和治疗,以确定最有效的方法。然而,人工智能(AI)和其他计算机科学领域的最新进展已经彻底改变了医疗领域,为加强疼痛管理提供了一种新颖而有前途的途径。本文综述了人工智能在慢性疼痛的诊断、评估和治疗中的潜在益处、局限性和前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utilizing Artificial Intelligence for the Diagnosis, Assessment, and Management of Chronic Pain.

Chronic pain is a prevalent condition and the leading cause of work absenteeism worldwide. This condition involves persistent pain lasting more than three months, significantly impacting the quality of life and social interactions of patients. While the causes of chronic pain can often remain unknown, no definitive cure exists for the various known causes. Furthermore, the evaluation and prediction of pain can be challenging, particularly in unconscious patients receiving care in the intensive care unit. Subjective measures and traditional methods are typically employed for diagnosis, assessment, and treatment to identify the most effective approach. However, recent advancements in Artificial Intelligence (AI) and other computer science fields have revolutionized the medical domain, offering a novel and promising avenue for enhancing pain management. This review provides an overview of the potential benefits, limitations, and prospects associated with the role of AI in the diagnosis, assessment, and management of chronic pain.

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来源期刊
Journal of Biomedical Physics and Engineering
Journal of Biomedical Physics and Engineering Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
2.90
自引率
0.00%
发文量
64
审稿时长
10 weeks
期刊介绍: The Journal of Biomedical Physics and Engineering (JBPE) is a bimonthly peer-reviewed English-language journal that publishes high-quality basic sciences and clinical research (experimental or theoretical) broadly concerned with the relationship of physics to medicine and engineering.
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