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本文引用的文献

1
Disparities in preventive health services among Somali immigrants and refugees.索马里移民和难民在预防保健服务方面的差异。
J Immigr Minor Health. 2012 Dec;14(6):968-74. doi: 10.1007/s10903-012-9632-4.
2
Diabetes care among Somali immigrants and refugees.索马里移民和难民的糖尿病护理。
J Community Health. 2012 Jun;37(3):680-4. doi: 10.1007/s10900-011-9499-7.
3
Automated identification of postoperative complications within an electronic medical record using natural language processing.利用自然语言处理技术在电子病历中自动识别术后并发症。
JAMA. 2011 Aug 24;306(8):848-55. doi: 10.1001/jama.2011.1204.
4
Discovering peripheral arterial disease cases from radiology notes using natural language processing.使用自然语言处理技术从放射学记录中发现外周动脉疾病病例。
AMIA Annu Symp Proc. 2010 Nov 13;2010:722-6.
5
Ethnic and racial health disparities research: issues and problems.种族与民族健康差异研究：问题与难题
Health Educ Behav. 2006 Aug;33(4):459-69. doi: 10.1177/1090198106287922.
6
State-based diabetes surveillance among minority populations.针对少数族裔人群的基于州的糖尿病监测。
Prev Chronic Dis. 2004 Apr;1(2):A03. Epub 2004 Mar 15.

通过自然语言处理追踪健康差距。

Tracking health disparities through natural-language processing.

机构信息

Division of Primary Care Internal Medicine, Mayo Clinic, Rochester, MN 55904, USA.

出版信息

Am J Public Health. 2013 Mar;103(3):448-9. doi: 10.2105/AJPH.2012.300943. Epub 2013 Jan 17.

DOI:10.2105/AJPH.2012.300943
PMID:23327237
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3673503/
Abstract

Health disparities and solutions are heterogeneous within and among racial and ethnic groups, yet existing administrative databases lack the granularity to reflect important sociocultural distinctions. We measured the efficacy of a natural-language-processing algorithm to identify a specific immigrant group. The algorithm demonstrated accuracy and precision in identifying Somali patients from the electronic medical records at a single institution. This technology holds promise to identify and track immigrants and refugees in the United States in local health care settings.

摘要

健康差异及其解决方案在不同种族和族裔群体内部和之间存在差异，但现有的行政数据库缺乏反映重要社会文化差异的粒度。我们衡量了自然语言处理算法识别特定移民群体的功效。该算法在识别单一机构电子病历中的索马里患者方面表现出了准确性和精度。这项技术有望在美国的当地医疗保健环境中识别和跟踪移民和难民。