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The structure of expert diagnostic knowledge in occupational medicine
Author(s) -
Harber Philip,
McCoy J. Michael,
Shimozaki Steven,
Coffman Phil,
Bailey Kevin
Publication year - 1991
Publication title -
american journal of industrial medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.7
H-Index - 104
eISSN - 1097-0274
pISSN - 0271-3586
DOI - 10.1002/ajim.4700190112
Subject(s) - medicine , occupational lung disease , occupational medicine , knowledge base , expert system , occupational disease , process (computing) , disease , occupational exposure , knowledge management , artificial intelligence , pathology , medical emergency , computer science , operating system
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.