title: The structure of expert diagnostic knowledge in occupational medicine.
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.
authors.affiliation: Department of Medicine, University of California Southern Occupational Health Center, Los Angeles.
authors.forename: P
authors.initials: P
authors.lastname: Harber
authors.forename: J M
authors.initials: JM
authors.lastname: McCoy
authors.forename: S
authors.initials: S
authors.lastname: Shimozaki
authors.forename: P
authors.initials: P
authors.lastname: Coffman
authors.forename: K
authors.initials: K
authors.lastname: Bailey
mesh_terms: D000465:Algorithms; D015982:Bias; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D005069:Evaluation Studies as Topic; D005103:Expert Systems / Q000295:instrumentation*; D006801:Humans; D008171:Lung Diseases / Q000175:diagnosis*; D009784:Occupational Diseases / Q000175:diagnosis*; D009787:Occupational Medicine / Q000295:instrumentation / Q000379:methods*