Biomedical subjects

T C Rindflesch

Publications and source records attributed to T C Rindflesch.

4 recordsLinked to original sources

PubMed1996

Finding the findings: identification of findings in medical literature using restricted natural language processing.

The ability to search the biomedical literature based on findings would provide enhanced access to information. We describe a computer program called FINDX which relies on the UMLS Metathesuaurus and restricted natural language processing to identify findings in free text. Such identification can serve as a filtering mechanism while selecting relevant papers. After discussing the salient characteristics of findings on which FINDX depends, we report on the results of an experiment in which we tested the program on a set of MEDLINE abstracts pertaining to the diagnosis of Parkinson Disease.

Humans↗

PubMed1994

Ambiguity resolution while mapping free text to the UMLS Metathesaurus.

We propose a method for resolving ambiguities encountered when mapping free text to the UMLS Metathesaurus. Much of the research in medical informatics involves the manipulation of free text. The Metathesaurus contains extensive information which supports solutions to problems encountered while processing such text. After discussing the process of mapping free text to the Metathesaurus and describing the ambiguities which are often the result of such mapping, we provide examples of rules designed to eliminate mapping ambiguities. These rules refer to the context in which the ambiguity occurs and crucially depend on semantic types obtained from the Metathesaurus. We have conducted a preliminary test of the methodology and the results obtained indicate that the rules successfully resolve ambiguity around 80% of the time.

Abstracting and Indexing↗

PubMed1993

Semantic processing in information retrieval.

Intuition suggests that one way to enhance the information retrieval process would be the use of phrases to characterize the contents of text. A number of researchers, however, have noted that phrases alone do not improve retrieval effectiveness. In this paper we briefly review the use of phrases in information retrieval and then suggest extensions to this paradigm using semantic information. We claim that semantic processing, which can be viewed as expressing relations between the concepts represented by phrases, will in fact enhance retrieval effectiveness. The availability of the UMLS domain model, which we exploit extensively, significantly contributes to the feasibility of this processing.

Information Storage and Retrieval↗

PubMed1993

UMLS knowledge for biomedical language processing.

This paper describes efforts to provide access to the free text in biomedical databases. The focus of the effort is the development of SPECIALIST, an experimental natural language processing system for the biomedical domain. The system includes a broad coverage parser supported by a large lexicon, modules that provide access to the extensive Unified Medical Language System (UMLS) Knowledge Sources, and a retrieval module that permits experiments in information retrieval. The UMLS Metathesaurus and Semantic Network provide a rich source of biomedical concepts and their interrelationships. Investigations have been conducted to determine the type of information required to effect a map between the language of queries and the language of relevant documents. Mappings are never straightforward and often involve multiple inferences.

Humans↗