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Volumn 15, Issue 4, 2009, Pages 259-265

Bayesian methods: A useful tool for classifying injury narratives into cause groups

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; CLASSIFICATION; COMPARATIVE STUDY; FACTUAL DATABASE; FUZZY LOGIC; HUMAN; INJURY; INTERNATIONAL CLASSIFICATION OF DISEASES; MEDICAL RECORD; METHODOLOGY; OCCUPATIONAL ACCIDENT; ORGANIZATION AND MANAGEMENT; PREDICTION AND FORECASTING; STATISTICS; WORKMAN COMPENSATION;

EID: 71549142879     PISSN: 13538047     EISSN: 14755785     Source Type: Journal    
DOI: 10.1136/ip.2008.021337     Document Type: Article
Times cited : (35)

References (14)
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    • Williamson A, Feyer AM, Stout N, et al. Use of narrative analysis for comparisons of the causes of fatal accidents in three countries: New Zealand, Australia, and the United States. Inj Prev 2001;7(Suppl 1):i15-20.
    • (2001) Inj Prev , vol.7 , Issue.SUPPL. 1
    • Williamson, A.1    Feyer, A.M.2    Stout, N.3
  • 2
    • 20444504318 scopus 로고    scopus 로고
    • Welding related occupational eye injuries: A narrative analysis
    • Lombardi DA, Pannala R, Sorock GS, et al. Welding related occupational eye injuries: a narrative analysis. Inj Prev 2005;11:174-9.
    • (2005) Inj Prev , vol.11 , pp. 174-9
    • Lombardi, D.A.1    Pannala, R.2    Sorock, G.S.3
  • 3
    • 0345328778 scopus 로고    scopus 로고
    • Computerized coding of injury narrative data from the National Health Interview Survey
    • Wellman HM, Lehto MR, Sorock GS. Computerized coding of injury narrative data from the National Health Interview Survey. Accid Anal Prev 2004;36:165-71.
    • (2004) Accid Anal Prev , vol.36 , pp. 165-71
    • Wellman, H.M.1    Lehto, M.R.2    Sorock, G.S.3
  • 4
    • 4444379856 scopus 로고    scopus 로고
    • Using narrative text and coded data to develop hazard scenarios for occupational injury interventions
    • Lincoln AE, Sorock GS, Courtney TK, et al. Using narrative text and coded data to develop hazard scenarios for occupational injury interventions. Inj Prev 2004;10:249-54.
    • (2004) Inj Prev , vol.10 , pp. 249-54
    • Lincoln, A.E.1    Sorock, G.S.2    Courtney, T.K.3
  • 5
    • 0003486554 scopus 로고
    • Bureau of Labor Statistics, Washington, DC: US Department of Labor, December
    • Bureau of Labor Statistics. Occupational injury and illness classification manual. Washington, DC: US Department of Labor, December 1992.
    • (1992) Occupational Injury and Illness Classification Manual
  • 6
    • 37749012689 scopus 로고    scopus 로고
    • Completeness and accuracy of International Classification of Disease (ICD) external cause of injury codes in emergency department electronic data
    • Hunt PR, Hackman H, Berenholz G, et al. Completeness and accuracy of International Classification of Disease (ICD) external cause of injury codes in emergency department electronic data. Inj Prev 2007;13:422-5.
    • (2007) Inj Prev , vol.13 , pp. 422-5
    • Hunt, P.R.1    Hackman, H.2    Berenholz, G.3
  • 7
    • 41249088907 scopus 로고    scopus 로고
    • Centers for Disease Control and Prevention (CDC). Strategies to improve external cause-of-injury coding in statebased hospital discharge and emergency department data systems: Recommendations of the CDC Workgroup for Improvement of External Cause-of-Injury Coding
    • Annest JL, Fingerhut LA, Gallagher SS, et al. Centers for Disease Control and Prevention (CDC). Strategies to improve external cause-of-injury coding in statebased hospital discharge and emergency department data systems: recommendations of the CDC Workgroup for Improvement of External Cause-of-Injury Coding. MMWR Recomm Rep 2008;57(RR-1):1-15.
    • (2008) MMWR Recomm Rep , vol.57 , Issue.RR-1 , pp. 1-15
    • Annest, J.L.1    Fingerhut, L.A.2    Gallagher, S.S.3
  • 9
    • 0002442796 scopus 로고    scopus 로고
    • Machine learning in automated text categorization
    • Sebastiani F. Machine learning in automated text categorization. ACM Computing Surveys (CSUR) 2002;34:1-47.
    • (2002) Acm Computing Surveys (CSUR) , vol.34 , pp. 1-47
    • Sebastiani, F.1
  • 13
    • 0030497863 scopus 로고    scopus 로고
    • Machine learning of motor vehicle accident categories from narrative data
    • Lehto MR, Sorock G. Machine learning of motor vehicle accident categories from narrative data. Methods Inf Med 1996;35:1-8.
    • (1996) Methods Inf Med , vol.35 , pp. 1-8
    • Lehto, M.R.1    Sorock, G.2
  • 14
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    • Motor vehicle crashes in roadway construction work zones: An analysis using narrative text from insurance claims
    • Sorock G, Ranney T, Lehto M. Motor vehicle crashes in roadway construction work zones: an analysis using narrative text from insurance claims. Accid Anal Prev 1996;28:131-8.
    • (1996) Accid Anal Prev , vol.28 , pp. 131-8
    • Sorock, G.1    Ranney, T.2    Lehto, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.