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Biomedical subjects

A T McCray

Publications and source records attributed to A T McCray.

31 records · Page 2Linked to original sources
PubMed1995

The representation of meaning in the UMLS.

The UMLS knowledge sources provide detailed information about biomedical naming systems and databases. The Metathesaurus contains biomedical terminology from an increasing number of biomedical thesauri, and the Semantic Network provides a structure that encompasses and unifies the thesauri that are included in the Metathesaurus. This paper addresses some fundamental principles underlying the design and development of the Metathesaurus and Semantic Network. It begins with a description of the formal properties of thesauri, including the Metathesaurus, and the formal properties of the Semantic Network. It continues with consideration of the principle of semantic locality and how this is reflected in the UMLS knowledge sources. The paper concludes with a discussion of the issues involved in attempting to re-use knowledge and the potential for re-use of the UMLS knowledge sources.

Artificial Intelligence↗
PubMed1994

Lexical methods for managing variation in biomedical terminologies.

Access to biomedical terminologies is hampered by the high degree of variability inherent in natural language terms and in the terminologies themselves. The lexicon, lexical programs, databases, and indexes included with the 1994 release of the UMLS Knowledge Sources are designed to help users manage this variability. We describe these resources and illustrate their flexibility and usefulness in providing enhanced access to data in the UMLS Metathesaurus.

Biology↗
PubMed1993

The Unified Medical Language System.

In 1986, the National Library of Medicine began a long-term research and development project to build the Unified Medical Language System (UMLS). The purpose of the UMLS is to improve the ability of computer programs to "understand" the biomedical meaning in user inquiries and to use this understanding to retrieve and integrate relevant machine-readable information for users. Underlying the UMLS effort is the assumption that timely access to accurate and up-to-date information will improve decision making and ultimately the quality of patient care and research. The development of the UMLS is a distributed national experiment with a strong element of international collaboration. The general strategy is to develop UMLS components through a series of successive approximations of the capabilities ultimately desired. Three experimental Knowledge Sources, the Metathesaurus, the Semantic Network, and the Information Sources Map have been developed and are distributed annually to interested researchers, many of whom have tested and evaluated them in a range of applications. The UMLS project and current developments in high-speed, high-capacity international networks are converging in ways that have great potential for enhancing access to biomedical information.

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↗
PubMed1991

Extending a natural language parser with UMLS knowledge.

Over the past several years our research efforts have been directed toward the identification of natural language processing methods and techniques for improving access to biomedical information stored in computerized form. To provide a testing ground for some of these ideas we have undertaken the development of SPECIALIST, a prototype system for parsing and accessing biomedical text. The system includes linguistic and biomedical knowledge. Linguistic knowledge involves rules and facts about the grammar of the language. Biomedical knowledge involves rules and facts about the domain of biomedicine. The UMLS knowledge sources, Meta-1 and the Semantic Network, as well as the UMLS test collection, have recently contributed to the development of the SPECIALIST system.

Information Storage and Retrieval↗
PubMed1990

Automated access to a large medical dictionary: online assistance for research and application in natural language processing.

Online dictionaries can be important tools for research and application in natural language processing. This paper describes work with a machine-readable version of "Dorland's Illustrated Medical Dictionary". First the characteristics of the dictionary are briefly described, and then the complex process of converting the tape to an online interactive dictionary is discussed. The results of several experiments in automatically deriving information from the online dictionary are presented, and the paper ends with a discussion of the use of the online dictionary as a tool in the development of a natural language processing system designed for the biomedical domain.

Abstracting and Indexing↗
PubMedDate not supplied

Planned NLM/AHCPR large-scale vocabulary test: using UMLS technology to determine the extent to which controlled vocabularies cover terminology needed for health care and public health.

The National Library of Medicine (NLM) and the Agency for Health Care Policy and Research (AHCPR) are sponsoring a test to determine the extent to which a combination of existing health-related terminologies covers vocabulary needed in health information systems. The test vocabularies are the 30 that are fully or partially represented in the 1996 edition of the Unified Medical Language System (UMLS) Metathesaurus, plus three planned additions: the portions of SNOMED International not in the 1996 Metathesaurus Read Clinical Classification, and the Logical Observations Identifiers, Names, and Codes (LOINC) system. These vocabularies are available to testers through a special interface to the Internet-based UMLS Knowledge Source Server. The test will determine the ability of the test vocabularies to serve as a source of controlled vocabulary for health data systems and applications. It should provide the basis for realistic resource estimates for developing and maintaining a comprehensive "standard" health vocabulary that is based on existing terminologies.

Computer Communication Networks↗
PubMedDate not supplied

Evaluating the coverage of controlled health data terminologies: report on the results of the NLM/AHCPR large scale vocabulary test.

OBJECTIVE: To determine the extent to which a combination of existing machine-readable health terminologies cover the concepts and terms needed for a comprehensive controlled vocabulary for health information systems by carrying out a distributed national experiment using the Internet and the UMLS Knowledge Sources, lexical programs, and server. METHODS: Using a specially designed Web-based interface to the UMLS Knowledge Source Server, participants searched the more than 30 vocabularies in the 1996 UMLS Metathesaurus and three planned additions to determine if concepts for which they desired controlled terminology were present or absent. For each term submitted, the interface presented a candidate exact match or a set of potential approximate matches from which the participant selected the most closely related concept. The interface captured a profile of the terms submitted by the participant and for each term searched, information about the concept (if any) selected by the participant. The term information was loaded into a database at NLM for review and analysis and was also available to be downloaded by the participant. A team of subject experts reviewed records to identify matches missed by participants and to correct any obvious errors in relationships. The editors of SNOMED International and the Read Codes were given a random sample of reviewed terms for which exact meaning matches were not found to identify exact matches that were missed or any valid combinations of concepts that were synonymous to input terms. The 1997 UMLS Metathesaurus was used in the semantic type and vocabulary source analysis because it included most of the three planned additions. RESULTS: Sixty-three participants submitted a total of 41,127 terms, which represented 32,679 normalized strings. More than 80% of the terms submitted were wanted for parts of the patient record related to the patient's condition. Following review, 58% of all submitted terms had exact meaning matches in the controlled vocabularies in the test, 41% had related concepts, and 1% were not found. Of the 28% of the terms which were narrower in meaning than a concept in the controlled vocabularies, 86% shared lexical items with the broader concept, but had additional modification. The percentage of exact meanings matches varied by specialty from 45% to 71%. Twenty-nine different vocabularies contained meanings for some of the 23,837 terms (a maximum of 12,707 discrete concepts) with exact meaning matches. Based on preliminary data and analysis, individual vocabularies contained < 1% to 63% of the terms and < 1% to 54% of the concepts. Only SNOMED International and the Read Codes had more than 60% of the terms and more than 50% of the concepts. CONCLUSIONS: The combination of existing controlled vocabularies included in the test represents the meanings of the majority of the terminology needed to record patient conditions, providing substantially more exact matches than any individual vocabulary in the set. From a technical and organizational perspective, the test was successful and should serve as a useful model, both for distributed input to the enhancement of controlled vocabularies and for other kinds of collaborative informatics research.

Evaluation Studies as Topic↗
PubMedDate not supplied

Design and implementation of a national clinical trials registry.

The authors have developed a Web-based system that provides summary information about clinical trials being conducted throughout the United States. The first version of the system, publicly available in February 2000, contains more than 4,000 records representing primarily trials sponsored by the National Institutes of Health. The impetus for this system has come from the Food and Drug Administration (FDA) Modernization Act of 1997, which mandated a registry of both federally and privately funded clinical trials "of experimental treatments for serious or life-threatening diseases or conditions." The system design and implementation have been guided by several principles. First, all stages of system development were guided by the needs of the primary intended audience, patients and other members of the public. Second, broad agreement on a common set of data elements was obtained. Third, the system was designed in a modular and extensible way, and search methods that take extensive advantage of the National Library of Medicine's Unified Medical Language System (UMLS) were developed. Finally, since this will be a long-term effort involving many individuals and organizations, the project is being implemented in several phases.

Clinical Trials as Topic↗