将患者对慢性疼痛的开放式叙述转化为定量措施:自然语言处理研究
Raquel Norel1, Jennifer Gewandter2, Zhengwu Zhang3
1IBM (United States), Yorktown Heights, NY, United States.
JMIR human factors
|November 25, 2025
概括
自然语言处理 (NLP) 可以通过分析患者叙述来量化慢性疼痛经历. 这种方法对了解主观疼痛强度和生活质量的临床应用有希望.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 计算语言学 计算语言学
- 数字健康数字健康
背景情况:
- 主观的患者报告对于评估慢性疼痛和治疗反应至关重要.
- 了解个人叙述提供了准确的洞察疾病的经历.
研究的目的:
- 应用自然语言处理 (NLP) 工具,从患者的疼痛叙述中得出定量指标.
- 评估NLP从20名慢性腰部疼痛 (CLBP) 患者的试点研究中从患者采访中提取有意义数据的能力.
主要方法:
- 通过半结构面试收集患者叙述,重点关注一般生活和CLBP经验.
- 利用NLP分析患者发言和来自验证疼痛问卷的句之间的语义关系.
- 与已建立的疼痛评估工具 (如数值评分尺度 (NRS) 和视觉模拟尺度 (VAS)) 相关联的NLP衍生措施.
主要成果:
- 患者叙述显示了语义接近验证的疼痛问卷概念.
- 语义距离与在NRS和VAS上报告的CLBP强度有很强的相关性.
- 在患有低和高疼痛水平的患者之间观察到语义指标的显著差异.
结论:
- 初步证据表明,NLP可以量化慢性疼痛的主观经验.
- 在疼痛评估方面,NLP有可能有新的临床应用.
- 需要进一步的研究来验证这些发现在更大,多样化的群体中.
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