对人工智能支持的干预措施进行范围审查,用于慢性风湿性疾病的非药物管理
Nirali Shah1, Alexis Castellanos1, Yen T Chen1
1University of Michigan, Ann Arbor, Michigan, USA.
Arthritis care & research
|July 14, 2025
概括
人工智能 (AI) 为慢性风湿性疾病提供了有希望的非药物干预措施,增强了教育和炼坚持. 然而,长期临床影响和症状管理需要进一步研究.
科学领域:
- 类风湿病学 类风湿病学
- 人工智能的人工智能
- 数字健康数字健康
背景情况:
- 慢性类风湿病影响全球数百万人,需要创新的非药物管理策略.
- 传统干预往往在坚持和长期有效性方面面临挑战.
- 人工智能 (AI) 提出了一种新的方法来支持患者的自我管理和治疗坚持.
研究的目的:
- 系统地审查和总结AI支持的非药物干预措施,用于慢性风湿性疾病的成年人.
- 详细介绍这些干预措施的组件,AI方法和证据基础.
- 评估人工智能干预对临床,心理和行为结果的影响.
主要方法:
- 在Embase,PubMed,Cochrane和Scopus数据库中进行全面的文献搜索.
- 包括所有类型的出版物和针对慢性风湿性疾病的成年人的干预设置.
- 数据提取研究特征,干预组件,人工智能方法和两位独立审查员的结果.
主要成果:
- 确定了15项人工智能支持的干预措施,主要针对骨关节炎 (73%),重点是教育和运动 (67%).
- 基于规则的专家系统 (40%) 是最常见的AI工具,其次是NLP (33%) 和机器学习 (27%).
- 干预措施显示了高的可用性,参与度和坚持性,在运动遵守,体育活动和症状方面有所改善,尽管长期可持续性不确定.
结论:
- 人工智能支持的干预措施显示出改善慢性风湿性疾病的教育,运动和行为指导的潜力.
- 有证据表明,AI工具具有很高的可用性和患者参与度.
- 人工智能干预对症状管理的长期临床影响仍然不确定,需要进一步研究.
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