Literature DB >> 20064794

Use of statistical analysis in the biomedical informatics literature.

Matthew Scotch1, Mona Duggal, Cynthia Brandt, Zhenqui Lin, Richard Shiffman.   

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.

Mesh:

Year:  2010        PMID: 20064794      PMCID: PMC2995622          DOI: 10.1197/jamia.M2853

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  3 in total

1.  Recommendations of the International Medical Informatics Association (IMIA) on education in health and medical informatics.

Authors: 
Journal:  Methods Inf Med       Date:  2000-08       Impact factor: 2.176

2.  A framework for the biomedical informatics curriculum.

Authors:  Stephen B Johnson
Journal:  AMIA Annu Symp Proc       Date:  2003

3.  Medicine residents' understanding of the biostatistics and results in the medical literature.

Authors:  Donna M Windish; Stephen J Huot; Michael L Green
Journal:  JAMA       Date:  2007-09-05       Impact factor: 56.272

  3 in total
  5 in total

1.  The use of count data models in biomedical informatics evaluation research.

Authors:  Jing Du; Young-Taek Park; Nawanan Theera-Ampornpunt; Jeffrey S McCullough; Stuart M Speedie
Journal:  J Am Med Inform Assoc       Date:  2011-06-29       Impact factor: 4.497

2.  Bibliometric analysis on retinoblastoma literatures in PubMed during 1929 to 2010.

Authors:  Zhi-Guang Zhao; Xue-Gang Guo; Chang-Tai Xu; Bo-Rong Pan; Li-Xian Xu
Journal:  Int J Ophthalmol       Date:  2011-04-18       Impact factor: 1.779

3.  Conduct Common Statistical Tests Online.

Authors:  Himel Mondal; Shaikat Mondal; Rabindranath Majumder; Rajesh De
Journal:  Indian Dermatol Online J       Date:  2022-06-24

4.  Bayesian Networks Analysis of Malocclusion Data.

Authors:  Marco Scutari; Pietro Auconi; Guido Caldarelli; Lorenzo Franchi
Journal:  Sci Rep       Date:  2017-11-10       Impact factor: 4.379

5.  An overview of the statistical methods reported by studies using the Canadian community health survey.

Authors:  Dean W Yergens; Daniel J Dutton; Scott B Patten
Journal:  BMC Med Res Methodol       Date:  2014-01-25       Impact factor: 4.615

  5 in total

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