Literature DB >> 26708801

Text mining describes the use of statistical and epidemiological methods in published medical research.

Christopher Meaney1, Rahim Moineddin2, Teja Voruganti3, Mary Ann O'Brien2, Paul Krueger2, Frank Sullivan4.   

Abstract

OBJECTIVE: To describe trends in the use of statistical and epidemiological methods in the medical literature over the past 2 decades. STUDY DESIGN AND
SETTING: We obtained all 1,028,786 articles from the PubMed Central Open-Access archive (retrieved May 9, 2015). We focused on 113,450 medical research articles. A Delphi panel identified 177 statistical/epidemiological methods pertinent to clinical researchers. We used a text-mining approach to determine if a specific statistical/epidemiological method was encountered in a given article. We report the proportion of articles using a specific method for the entire cross-sectional sample and also stratified into three blocks of time (1995-2005; 2006-2010; 2011-2015).
RESULTS: Numeric descriptive statistics were commonplace (96.4% articles). Other frequently encountered methods groups included statistical inferential concepts (52.9% articles), epidemiological measures of association (53.5% articles) methods for diagnostic/classification accuracy (40.1% articles), hypothesis testing (28.8% articles), ANOVA (23.2% articles), and regression (22.6% articles). We observed relative percent increases in the use of: regression (103.0%), missing data methods (217.9%), survival analysis (147.6%), and correlated data analysis (192.2%).
CONCLUSIONS: This study identified commonly encountered and emergent methods used to investigate medical research problems. Clinical researchers must be aware of the methodological landscape in their field, as statistical/epidemiological methods underpin research claims.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bibliometrics; Epidemiological methods; Medical research; PubMed; Statistical methods; Text mining

Mesh:

Year:  2015        PMID: 26708801     DOI: 10.1016/j.jclinepi.2015.10.020

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  2 in total

1.  Text Mining of Journal Articles for Sleep Disorder Terminologies.

Authors:  Calvin Lam; Fu-Chih Lai; Chia-Hui Wang; Mei-Hsin Lai; Nanly Hsu; Min-Huey Chung
Journal:  PLoS One       Date:  2016-05-20       Impact factor: 3.240

2.  LASSO Regression Modeling on Prediction of Medical Terms among Seafarers' Health Documents Using Tidy Text Mining.

Authors:  Nalini Chintalapudi; Ulrico Angeloni; Gopi Battineni; Marzio di Canio; Claudia Marotta; Giovanni Rezza; Getu Gamo Sagaro; Andrea Silenzi; Francesco Amenta
Journal:  Bioengineering (Basel)       Date:  2022-03-17
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.