使用自然语言处理对文本中的同理心识别进行范围审查
Vishal Anand Shetty1, Shauna Durbin2, Meghan S Weyrich3
1Department of Health Promotion and Policy, University of Massachusetts, Amherst, MA 01003, United States.
Journal of the American Medical Informatics Association : JAMIA
|December 13, 2023
概括
这篇评论探讨了自然语言处理 (NLP) 对于识别文本中的同理心. 虽然NLP对医生与患者的沟通有希望,但定义和测量同情心仍然具有挑战性.
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
- 医疗信息学 医疗信息学
背景情况:
- 在医疗保健中,同情的沟通至关重要.
- 患者门户越来越多地用于医生与患者的互动.
- 在文本中自动识别同情是一种新兴领域.
研究的目的:
- 通过NLP,对使用NLP在文本中的同理心识别研究进行范围审查.
- 在患者门户消息中为识别医生同情沟通的方法提供信息.
主要方法:
- 在2023年5月1日之前,对6个相关研究数据库进行系统搜索.
- 通过标题选,摘要审查和全文审查进行研究选择.
- 在审查过程中遵守PRISMA-ScR指南.
主要成果:
- 在2446篇出版物中选出了39篇研究.
- 概括了同理心的定义,数据源,测试模型和模型性能.
- 观察到NLP在同理心任务中的转向基于变压器的模型的转变.
结论:
- 目前的NLP方法显示出与同理心相关的任务的潜力.
- 在文本中准确地定义和测量同情心仍然存在挑战.
- 对于患者与医生的沟通研究,需要进一步考虑同情的概念化.
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