A medical information resource server: one stop shopping on the Internet.
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Computer Communication Networks↗
Biomedical subjects
J A Gnassi
Publications and source records attributed to J A Gnassi.
A pre-search estimation algorithm for MEDLINE strategies with qualifiers.
Inexperienced users of online medical databases often have difficulty formulating their queries. Systems designed to assist them usually do not estimate how effective the initial search strategy will be before performing an actual search. Consequently, the search may find an overwhelming number of citations, or retrieve nothing at all. We have developed an estimation algorithm to predict the outcome of a MEDLINE search. The portion of the algorithm described here estimates retrieval for strategies containing qualifiers. In test searches, the estimate reduced the trial-and-error of strategy formulation. However, the accuracy of the estimate fell short of expectations. Our results show that pre-search estimation for strategies with qualifiers cannot be performed effectively with only the occurrence data that is presently available. They further imply that automated search intermediaries can benefit from medical knowledge which expresses the relationships that exist between terms.
Algorithms↗
A survey of electronic drug information resources and identification of problems associated with the differing vocabularies used to key them.
Drug information resources are increasingly becoming electronically available. They differ in scope, granularity, and purpose. These considerations have shaped the selection of dissimilar drug name keys, complicating access. An abbreviated and simplified historical context of the development of official controlled vocabularies and their relationships is followed by a review of the kinds of information available in several electronic drug information resources. The key vocabularies used are discussed with examples. Problems using the differing terms of the resource vocabularies are identified.
Abstracting and Indexing↗
Q & A: a query formulation assistant.
Inexperienced users of online medical databases often do not know how to formulate their queries for effective searches. Previous attempts to help them have provided some standard procedures for query formulation, but depend on the user to enter the concepts of a query properly so that the correct search strategy will be formed. Intelligent assistance specific to a particular query often is not given. Several systems do refine the initial strategy based on relevance feedback, but usually do not make an effort to determine how well-formed a query is before actually performing the search. As part of the Interactive Query Workstation (IQW), we have developed an expert system, Questions and Answers (Q&A), that assists in formulating an initial strategy given concepts entered by the user and that determines if the strategy is well-formed, refining it when necessary.
Expert Systems↗
Interactive query workstation: a demonstration of the practical use of UMLS knowledge sources.
The Interactive Query Workstation (IQW) has been developed to provide clinicians with a uniform program interface for retrieving medical-related information from various computer-based information resources. These resources can vary in content (bibliographic databases, drug information, general medical text databases), function (article retrieval, differential diagnosis, drug interaction detection, or drug dosage and administration information), and media formats (local hard disk, CD-ROM, local area network, or distant telecommunication link). IQW allows modular addition of new resources as well as extension of previously installed resources. The National Library of Medicine's three Unified Medical Language System (UMLS) Knowledge Sources, the Metathesaurus (Meta), the Semantic Network, and the Information Sources Map (ISM) have been incorporated into many aspects of IQW. Meta provides information about medical terminology and aids IQW in isolating the basic concepts from a clinician's question. The Semantic Network provides information about the categorization of concepts and possible relations between concepts. It also assists IQW in determining which queries are appropriate for a set of concepts contained in the clinician's question. The ISM provides information about the content available from a computer-based resources and aids IQW in selecting an appropriate resource from which to collect information. The computer-based resource selection is performed without user intervention. This interactive demonstration shows an environment which increases the accessibility of medical information to clinicians by utilizing the three UMLS Knowledge Sources.
Information Storage and Retrieval↗