title: Predicate calculus, artificial intelligence, and workers' compensation.
abstract: Application of principles of predicate calculus (PC) and artificial intelligence (AI) search methods to occupational medicine can meet several goals. First, they can improve understanding of the diagnostic process and recognition of the sources of uncertainty in knowledge and in case specific information. Second, PC provides a rational means of resolving differences in conclusion based upon the same premises. Third, understanding of these principles allows separation of knowledge (facts) from the process by which they are used and therefore facilitates development of AI-based expert systems. Application of PC to recognizing causation of pulmonary fibrosis is demonstrated in this paper, providing a method that can be generalized to other problems in occupational medicine. Application of PC and understanding of AI search routines may be particularly applicable to workers' compensation where explicit statement of rational and inferential process is necessary. This approach is useful in the diagnosis of occupational lung disease and may be particularly valuable in workers' compensation considerations, wherein explicit statement of rationale is needed.
authors.affiliation: Occupational Medicine Branch/Pulmonary Division, University of California, Los Angeles.
authors.forename: P
authors.initials: P
authors.lastname: Harber
authors.forename: J M
authors.initials: JM
authors.lastname: McCoy
mesh_terms: D001185:Artificial Intelligence; D001195:Asbestosis / Q000175:diagnosis; D002140:California; D003937:Diagnosis, Differential; D006801:Humans; D008128:Logic; D008433:Mathematics; D009784:Occupational Diseases / Q000175:diagnosis*; D011658:Pulmonary Fibrosis / Q000175:diagnosis; D012307:Risk Factors; D014942:Workers' Compensation