Examination of Disease Names Using Non-Abelian Symbolic Logic - Moore, G. W.; Hutchins, G. M.; Miller, R. E. (Methods of Information in Medicine, 1986)
SummaryDespite many investigations of the potential role of formal symbolic logic in medicine, little attention has been paid to the distribution of words in large quantities of natural language text and how this might affect the choice of a logic system. With the emergence of communicating word processor technology, it is now possible to enter large amounts of routine medical text in computer-readable form and study its implications for symbolic logic formalisms.We examined the word distribution in the Anatomical Diagnosis reports of 7,000 consecutive autopsied patients from the Department of Pathology of The Johns Hopkins Hospital. We found that uncommon disease entities consisting of common component words were best recovered using a search algorithm which examines conjunction (and) logic in ascending order of word frequency and alternation (inclusive or) logic in descending order of word frequency. This logic is non-Abelian, non-distributive, and associative for conjunction but not for alternation. Our results suggest that natural language text analysis, which is essential for studying medical documents by computer, may require heretofore little studied variant forms of symbolic logic.
Keywords: Natural Language Text Analysis; Symbolic Logic; Autopsy Protocol