非洲公共卫生中的自然语言处理技术:范围审查
Songbo Hu1, Abigail Oppong1, Ebele Mogo2
1Language Technology Lab, University of Cambridge, Cambridge, United Kingdom.
Journal of medical Internet research
|March 7, 2025
概括
自然语言处理 (NLP) 在非洲显示出公共卫生潜力,但在语言包容性和部署方面面临挑战. 研究强调了支持各种非洲语言和将NLP整合到卫生系统中的差距,以获得可衡量的影响.
科学领域:
- 公共卫生信息学 公共卫生信息学
- 计算语言学 计算语言学
- 卫生系统研究 卫生系统研究
背景情况:
- 自然语言处理 (NLP) 为推进公共卫生倡议提供了巨大的潜力.
- 然而,在非洲卫生系统中NLP的应用受到有限的数字基础设施和计算资源的阻碍,特别是关于非洲大陆的语言多样性.
研究的目的:
- 进行范围审查,对非洲公共卫生中的NLP技术的证据进行映射.
- 确定解决的公共卫生需求,影响因素,部署阶段,整合水平和NLP技术的可测量影响.
- 综合建议,以提高非洲与健康相关的NLP的质量,成本和可访问性.
主要方法:
- 从2013年1月到2024年10月,在主要数据库 (MEDLINE,ACL Anthology,Scopus,IEEE Xplore,ACM数字图书馆) 中对学术和灰色文学进行系统的文献搜索.
- 数据提取和NLP功能映射到世卫组织基本公共卫生功能和联合国可持续发展目标.
- 根据PRISMA-ScR指导方针进行分析,并使用公开可用的协议.
主要成果:
- 包括54项研究,显示语言覆盖范围不均,对主要非洲语言的支持有限,对非洲大陆的2000多种语言的支持很少.
- 大多数NLP技术都处于原型设计阶段,只有一个完全部署的聊天机器人;可测量的公共卫生影响的证据很少 (4%的研究).
- 建议强调扩大语言支持,解决当地需求,建立信任,将解决方案整合到卫生系统中,并使用参与式设计.
结论:
- 在部署,语言包容性和NLP对非洲公共卫生的健康结果评估方面仍然存在重大差距.
- 未来的研究必须采用跨部门,基于需求的方法,让当地社区参与,与现有卫生系统保持一致,并包括严格的评估,以改善公共卫生结果.
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