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为公共卫生实践设计机器翻译应用程序的建模工作流程。

Modeling workflow to design machine translation applications for public health practice.

作者信息

Turner Anne M, Brownstein Megumu K, Cole Kate, Karasz Hilary, Kirchhoff Katrin

机构信息

University of Washington Northwest Center for Public Health Practice, 1107 NE 45th Street, Suite 400, Box 354809, Seattle, WA 98105, USA; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA; Department of Health Services, University of Washington, Seattle, WA, USA.

University of Washington Northwest Center for Public Health Practice, 1107 NE 45th Street, Suite 400, Box 354809, Seattle, WA 98105, USA.

出版信息

J Biomed Inform. 2015 Feb;53:136-46. doi: 10.1016/j.jbi.2014.10.005. Epub 2014 Oct 17.

DOI:10.1016/j.jbi.2014.10.005
PMID:25445922
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4355243/
Abstract

OBJECTIVE

Provide a detailed understanding of the information workflow processes related to translating health promotion materials for limited English proficiency individuals in order to inform the design of context-driven machine translation (MT) tools for public health (PH).

MATERIALS AND METHODS

We applied a cognitive work analysis framework to investigate the translation information workflow processes of two large health departments in Washington State. Researchers conducted interviews, performed a task analysis, and validated results with PH professionals to model translation workflow and identify functional requirements for a translation system for PH.

RESULTS

The study resulted in a detailed description of work related to translation of PH materials, an information workflow diagram, and a description of attitudes towards MT technology. We identified a number of themes that hold design implications for incorporating MT in PH translation practice. A PH translation tool prototype was designed based on these findings.

DISCUSSION

This study underscores the importance of understanding the work context and information workflow for which systems will be designed. Based on themes and translation information workflow processes, we identified key design guidelines for incorporating MT into PH translation work. Primary amongst these is that MT should be followed by human review for translations to be of high quality and for the technology to be adopted into practice.

CONCLUSION

The time and costs of creating multilingual health promotion materials are barriers to translation. PH personnel were interested in MT's potential to improve access to low-cost translated PH materials, but expressed concerns about ensuring quality. We outline design considerations and a potential machine translation tool to best fit MT systems into PH practice.

摘要

目的

详细了解与为英语水平有限的人群翻译健康促进材料相关的信息工作流程,以便为公共卫生领域上下文驱动的机器翻译(MT)工具的设计提供参考。

材料与方法

我们应用认知工作分析框架来研究华盛顿州两个大型卫生部门的翻译信息工作流程。研究人员进行了访谈、任务分析,并与公共卫生专业人员验证结果,以构建翻译工作流程模型并确定公共卫生翻译系统的功能需求。

结果

该研究得出了与公共卫生材料翻译相关工作的详细描述、一个信息工作流程图以及对机器翻译技术的态度描述。我们确定了一些对在公共卫生翻译实践中纳入机器翻译具有设计启示的主题。基于这些发现设计了一个公共卫生翻译工具原型。

讨论

本研究强调了理解系统设计所针对的工作环境和信息工作流程的重要性。基于主题和翻译信息工作流程,我们确定了将机器翻译纳入公共卫生翻译工作的关键设计准则。其中首要的是,为了获得高质量的翻译并使该技术得以实际应用,机器翻译之后应进行人工审核。

结论

制作多语言健康促进材料的时间和成本是翻译的障碍。公共卫生人员对机器翻译在改善获取低成本翻译公共卫生材料方面的潜力感兴趣,但对确保质量表示担忧。我们概述了设计考量因素以及一种潜在的机器翻译工具,以使机器翻译系统最适合公共卫生实践。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eb6/4355243/0d4fb430d1f5/nihms-636020-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eb6/4355243/0d4fb430d1f5/nihms-636020-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eb6/4355243/0d4fb430d1f5/nihms-636020-f0001.jpg

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Local health department translation processes: potential of machine translation technologies to help meet needs.地方卫生部门的翻译流程:机器翻译技术助力满足需求的潜力。
AMIA Annu Symp Proc. 2013 Nov 16;2013:1378-85. eCollection 2013.
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A comparison of human and machine translation of health promotion materials for public health practice: time, costs, and quality.用于公共卫生实践的健康促进材料的人工翻译与机器翻译比较:时间、成本和质量
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Understanding the work of pediatric inpatient medicine teams: implications for information system requirements.了解儿科住院医疗团队的工作:对信息系统需求的影响。
AMIA Annu Symp Proc. 2011;2011:455-64. Epub 2011 Oct 22.
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