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生物医学信息学文献中的统计分析应用。

Use of statistical analysis in the biomedical informatics literature.

机构信息

Yale Center for Medical Informatics, Yale University, New Haven, Connecticut 06511, USA.

出版信息

J Am Med Inform Assoc. 2010 Jan-Feb;17(1):3-5. doi: 10.1197/jamia.M2853.

Abstract

Statistics is an essential aspect of biomedical informatics. To examine the use of statistics in informatics research, a literature review of recent articles in two high-impact factor biomedical informatics journals, the Journal of American Medical Informatics Association (JAMIA) and the International Journal of Medical Informatics was conducted. The use of statistical methods in each paper was examined. Articles of original investigations from 2000 to 2007 were reviewed. For each journal, the results by statistical methods were analyzed as: descriptive, elementary, multivariable, other regression, machine learning, and other statistics. For both journals, descriptive statistics were most often used. Elementary statistics such as t tests, chi(2), and Wilcoxon tests were much more frequent in JAMIA, while machine learning approaches such as decision trees and support vector machines were similar in occurrence across the journals. Also, the use of diagnostic statistics such as sensitivity, specificity, precision, and recall, was more frequent in JAMIA. These results highlight the use of statistics in informatics and the need for biomedical informatics scientists to have, as a minimum, proficiency in descriptive and elementary statistics.

摘要

统计学是生物医学信息学的一个重要方面。为了考察统计学在信息学研究中的应用,对两份高影响力因子的生物医学信息学杂志,即美国医学信息学会杂志(JAMIA)和国际医学信息学杂志(International Journal of Medical Informatics)中的近期文章进行了文献综述。对每篇论文中使用的统计方法进行了检查。对 2000 年至 2007 年的原始研究文章进行了回顾。对于每个杂志,根据统计方法的结果进行了分析,包括描述性、基本、多变量、其他回归、机器学习和其他统计学方法。对于两个杂志,描述性统计方法最常用。基本统计方法,如 t 检验、卡方检验和 Wilcoxon 检验,在 JAMIA 中更为常见,而机器学习方法,如决策树和支持向量机,在两个杂志中的出现频率相似。此外,诊断统计方法,如灵敏度、特异性、精度和召回率,在 JAMIA 中更为常用。这些结果突出了统计学在信息学中的应用,也需要生物医学信息学科学家至少精通描述性和基本统计学方法。

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