Literature DB >> 25221787

Computer-Based Coding of Occupation Codes for Epidemiological Analyses.

Daniel E Russ1, Kwan-Yuet Ho1, Calvin A Johnson1, Melissa C Friesen2.   

Abstract

Mapping job titles to standardized occupation classification (SOC) codes is an important step in evaluating changes in health risks over time as measured in inspection databases. However, manual SOC coding is cost prohibitive for very large studies. Computer based SOC coding systems can improve the efficiency of incorporating occupational risk factors into large-scale epidemiological studies. We present a novel method of mapping verbatim job titles to SOC codes using a large table of prior knowledge available in the public domain that included detailed description of the tasks and activities and their synonyms relevant to each SOC code. Job titles are compared to our knowledge base to find the closest matching SOC code. A soft Jaccard index is used to measure the similarity between a previously unseen job title and the knowledge base. Additional information such as standardized industrial codes can be incorporated to improve the SOC code determination by providing additional context to break ties in matches.

Entities:  

Keywords:  Automated Coding; Occupational Coding

Year:  2014        PMID: 25221787      PMCID: PMC4161468          DOI: 10.1109/CBMS.2014.79

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Comput Based Med Syst        ISSN: 2372-918X


  1 in total

1.  Workplace measurements by the U.S. Occupational Safety and Health Administration since 1979: Descriptive analysis and potential uses for exposure assessment.

Authors:  J Lavoue; M C Friesen; I Burstyn
Journal:  Ann Occup Hyg       Date:  2013-06
  1 in total
  3 in total

1.  Development of a Coding and Crosswalk Tool for Occupations and Industries.

Authors:  Thomas Rémen; Lesley Richardson; Corinne Pilorget; Gilles Palmer; Jack Siemiatycki; Jérôme Lavoué
Journal:  Ann Work Expo Health       Date:  2018-08-13       Impact factor: 2.179

2.  Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies.

Authors:  Daniel E Russ; Kwan-Yuet Ho; Joanne S Colt; Karla R Armenti; Dalsu Baris; Wong-Ho Chow; Faith Davis; Alison Johnson; Mark P Purdue; Margaret R Karagas; Kendra Schwartz; Molly Schwenn; Debra T Silverman; Calvin A Johnson; Melissa C Friesen
Journal:  Occup Environ Med       Date:  2016-04-21       Impact factor: 4.402

3.  Hippocampal representations for deep learning on Alzheimer's disease.

Authors:  Ignacio Sarasua; Sebastian Pölsterl; Christian Wachinger
Journal:  Sci Rep       Date:  2022-05-21       Impact factor: 4.996

  3 in total

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