The structure of expert diagnostic knowledge in occupational medicine

Philip Harber, J. Michael McCoy, Steven Shimozaki, Phil Coffman, Kevin Bailey

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Development of an artificial intelligence expert system for diagnosing occupational lung disease requires explicit specification of the structure of knowledge necessary in clinical occupational medicine independent of the process by which the knowledge is utilized. Furthermore, explicit recognition of sources of uncertainty is necessary. Seven categories of knowledge define the diagnostic knowledge base in occupational pulmonary medicine. These include four objects (jobs, industries, exposures, and diseases) and three relationships between pairs of objects. This analysis demonstrates some of the unique aspects of occupational medicine expertise.

Original languageEnglish (US)
Pages (from-to)109-120
Number of pages12
JournalAmerican Journal of Industrial Medicine
Volume19
Issue number1
DOIs
StatePublished - 1991

Keywords

  • artificial intelligence (AI)
  • computermethods
  • decision support
  • expert system
  • occupational lung disease
  • occupational medicine
  • pulmonary disease

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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