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Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks

机译:电子病历中人口规模表型学数据的比较分析揭示了特定种族的疾病网络

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Motivation: Underrepresentation of racial groups represents an important challenge and major gap in phenomics research. Most of the current human phenomics research is based primarily on European populations; hence it is an important challenge to expand it to consider other population groups. One approach is to utilize data from EMR databases that contain patient data from diverse demographics and ancestries. The implications of this racial underrepresentation of data can be profound regarding effects on the healthcare delivery and actionability. To the best of our knowledge, our work is the first attempt to perform comparative, population-scale analyses of disease networks across three different populations, namely Caucasian (EA), African American (AA) and Hispanic/Latino (HL).
机译:动机:种族群体代表性不足代表着表象学研究的重要挑战和重大空白。当前大多数人类表态学研究主要基于欧洲人口。因此,将其扩展到考虑其他人群是一个重要的挑战。一种方法是利用EMR数据库中的数据,其中包含来自不同人口统计和祖先的患者数据。种族歧视性数据不足对医疗保健交付和可操作性的影响具有深远的意义。据我们所知,我们的工作是对白种人(EA),非裔美国人(AA)和西班牙裔/拉丁美洲裔(HL)这三个不同人群进行疾病网络比较,人群规模分析的首次尝试。

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