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An automatic method for classifying medical researchers into domain specific subgroups.

机译:一种将医学研究人员分类为特定领域子组的自动方法。

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Objective. This dissertation developed an automatic classification procedure, as an example of a novel tool for an informationist, which extracts information from published abstracts, classifies abstracts into their "fields of study," and then determines the researcher's "field of study" and "level of activity.";Method. This dissertation compared a domain expert's method of classification and an automatic classification procedure on a random sample of 101 medical researchers (derived from a potential list of 305 medical researchers) and their associated abstracts.;Design. The study design is a retrospective, cross-sectional, inter-rater agreement study, designed to compare two classification methods (i.e., automatic classification procedure and domain expert). The study population consists of University of Pittsburgh, School of Medicine, Department of Medicine (DOM) professionals who (1) have published at least one article listed in PubMedRTM as first or last author and/or (2) are the primary investigator for at least one grant listed in CRISP.;Main outcome measures. Three outcome measures were derived from the domain expert's versus automatic categorization procedure: (1) an abstract's "field of study," (2) a researcher's "field of study" and (3) a researcher's "level of activity and field of study.";Results. Kappa showed moderate agreement between automatic and domain expert classification for the abstracts' "field of study" (Kappa = 0.535, n = 504, p .000). Kappa showed moderate agreement between automatic and domain expert classification of the researcher's "field of study" (Kappa = 0.535, n = 101, p .000). Kappa showed good agreement between automatic and domain expert classification of the researcher's "level of activity and field of study" (Kappa = 0.634, n = 101, p .000).;Conclusion. The study suggests that an automatic library classification procedure can provide rapid classification of medical research abstracts into their "fields of study." The classification procedure can also process multiple abstracts' "fields of study" and classify their associated medical researchers into their "field of study" and "level of activity and field of study." The classification procedure, used as a tool by an informationist, can be used as the basis for new services.
机译:目的。本文开发了一种自动分类程序,作为信息学家的一种新颖工具,该工具从发布的摘要中提取信息,将摘要分类为“研究领域”,然后确定研究者的“研究领域”和“研究水平”。活动。”;方法。本文比较了领域专家的分类方法和自动分类程序,对101名医学研究人员的随机样本(来自305名医学研究人员的潜在列表)及其相关摘要进行了设计。研究设计是一项回顾性,横断面,评估者之间的一致性研究,旨在比较两种分类方法(即自动分类程序和领域专家)。研究人群由匹兹堡大学医学院,医学系(DOM)专业人员组成,他们(1)发表了至少一篇发表在PubMedRTM上的文章作为第一作者或最后作者,和/或(2)是该研究的主要研究者CRISP中列出的至少一项赠款。主要成果指标。从领域专家的对自动分类过程中得出了三种结果度量:(1)摘要的“研究领域”,(2)研究者的“研究领域”,以及(3)研究者的“活动水平和研究领域”。 “;结果。对于摘要的“研究领域”,Kappa显示出自动和领域专家分类之间的适度一致(Kappa = 0.535,n = 504,p <.000)。 Kappa在研究者的“研究领域”的自动分类和领域专家分类之间显示出适度的一致性(Kappa = 0.535,n = 101,p <.000)。 Kappa在研究人员的“活动水平和研究领域”的自动分类和领域专家分类之间显示出很好的一致性(Kappa = 0.634,n = 101,p <.000)。研究表明,自动图书馆分类程序可以将医学研究摘要快速分类到其“研究领域”。分类程序还可以处理多个摘要的“研究领域”,并将其关联的医学研究人员分类为他们的“研究领域”,“活动水平和研究领域”。信息员用作工具的分类程序可以用作新服务的基础。

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