Ihc Health Services

Spencer B Koehler

Peter J Haug

Michael L Gundersen

Rudy E Van Bree

Lee M Christensen

A natural language understanding system is described to provide generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, is implemented by means of a Bayesian network, and is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its &ldquo;deep&rdquo; or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics.

Probabilistic system for natural language processing

A natural language understanding system is described which provides for the generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, in the preferred embodiment of the invention implemented by means of a Bayesian network, is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its &ldquo;deep&rdquo; or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics. In the preferred embodiment of the invention, spell checking and transformational processing as well as semantic analysis make use of semantic probabilistic determinations.

Probabilistic method for natural language processing and for encoding free-text data into a medical database by utilizing a Bayesian network to perform spell checking of words

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Orem, UT, United States of America

Spencer B Koehler