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人工智能用于预测脊椎疾病干预性疼痛药物的临床结果:系统性审查

Puneet Gupta¹, Stephen Richards¹, Sina Davari Farid¹

¹Department of Anesthesiology and Critical Care Medicine, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.

Pain practice : the official journal of World Institute of Pain

|February 23, 2026

概括

人工智能 (AI) 模型在预测脊髓干预结果方面表现有前途,例如外围注射类固醇和脊髓刺激器. 然而,当前的人工智能模型需要提高性能和外部验证才能可靠的临床使用.

科学领域:

疼痛医学医学疼痛医学
干预性脊柱手术干预性脊柱手术
人工智能应用程序人工智能应用程序

背景情况:

人工智能 (AI) 为分析疼痛医学中复杂数据提供了先进的功能.
越来越需要评估AI在开发干预性脊柱疾病临床预测模型中的作用.
了解人工智能在这个领域的现状对于未来的进步至关重要.

研究的目的:

系统地审查基于人工智能的预测模型,用于干预脊柱医学中的临床结果.
分析这些人工智能模型的应用,性能和通用性.
为了识别差距,并指导未来的AI研究脊柱干预.

主要方法:

在PubMed/MEDLINE和Scopus数据库中发表的研究的系统审查.
资格标准侧重于基于人工智能的临床预测模型,用于干预性脊柱医学.
数据提取包括模型应用,性能指标 (AUROC,准确性) 和验证 (内部/外部).

主要成果:

九项研究符合纳入标准,重点是外周注射类固醇 (4项研究) 和脊髓刺激剂 (5项研究).
只有两项研究 (22.2%) 报告了AI模型的出色性能 (AUROC/精度>0.90).
一项单一的研究 (11.1%) 报告了其AI模型的外部验证.

结论:

目前,人工智能在干预性脊柱医学中的应用主要局限于外周类固醇注射和脊髓刺激器.
显著需要提高人工智能模型的性能和通用性.
在AI预测模型在脊柱护理中的广泛临床翻译之前,外部验证至关重要.

关键词:

人工智能的人工智能是人工智能.慢性背部疼痛慢性背部疼痛干预性脊柱干预干预性脊柱干预预测模型预测模型

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