A vocabulary for medical informatics

Hierarchical Distribution Analysis for Computer-assisted Classifications of Patient Records

The many existing hierarchical classifications present opportunities for computer-aided classification of medical data. The authors evaluate lexical term mapping followed by hierarchical node activation to determine the semantic locality of diagnoses in the American College of Radiology (ACR) classification. The activated hierarchy exposes conceptual structures behind lexically matched categories and markedly narrows the alternatives for human review. Several distribution analyses are evaluated for narrowing the candidate search space, to reduce ambiguity. The methods were tested on a prototype system, using a set of 78 samples of Mayo radiology diagnoses; their relative effectiveness is illustrated.

Identifying a core set of medical informatics serials: an analysis using the MEDLINE database

A study was undertaken to test the hypothesis that a core set of medical informatics serials could be identified by using standard bibliometric techniques. All journal articles indexed by the National Library of Medicine between 1990 and 1994 were included. Articles were identified by using the "MEDICAL INFORMATICS" Medical Subject Heading (MeSH) term. Each serial title containing articles was then ranked according to (1) the total number of medical informatics journal articles indexed and (2) the percentage of medical informatics journal articles indexed. Twenty-eight serials had more than 100 articles indexed under the "MEDICAL INFORMATICS" MeSH term. Thirty serials had more than 40% of their articles indexed under the "MEDICAL INFORMATICS" MESH term. A "core" set of fourteen serials had 100 or more medical informatics articles indexed, including more than 70% of all articles they published. The methodology described provides librarians with another tool to use in the difficult task of journal selection. The set of "core" serials identified provides librarians with a ranked list of serials, based on which a medical informatics collection can be developed.

Approaches to the construction of a medical informatics glossary and thesaurus

In a project concerned with establishing a glossary and thesaurus for the medical informatics domain, various approaches to the task have been investigated. The developers take the view that a glossary should be a coherent system of terms, reflecting a coherent system of concepts that underlies a body of knowledge about a domain. A framework for the conceptual analysis of the concepts/terms underlying the domain has been developed. The emphasis of this framework is on how the concepts relate together. This work has given an important insight into how the practical task of establishing well-structured vocabularies for a field can be better achieved. An eclectic approach to term selection was adopted. Criteria for assessing what constitutes good definitions for concepts in a field were examined. Using all these approaches glossaries, thesauri and domain models of the medical informatics field are being developed. Another aspect of our work of particular interest is the development of attributed definitions from which inheritance patterns can be defined.

Computer-assisted dynamic integration of multiple medical thesauruses

We have previously described a user-interactive rule-based computer program (Dyna-SaurI) designed for dynamic thesaurus integration, and demonstrated its efficacy on integrating dermatological subsets of the MeSH and SNOMED thesauruses. In the present study, we have refined our rules for merging and mapping multiple thesauruses and tested these rules. We then applied them with a set of optimized parameters to the integration of a third thesaurus, a subset of the International Coding Index for Dermatology, with the Integrated MeSH-SNOMED thesaurus. The parameter changes resulted in improved ranking of more specific and conceptually closer terms.

Citation analysis of the field of medical decision making: update, 1959-1985

This article updates a prior citation analysis of medical decision making, published in this journal in 1984. Building on the original core list, decision making papers were added based on any of three criteria: citation of three papers already on the list, identification by a MEDLINE search (CATLINE for books) as relevant to the topic, or mention in a recent review article on decision analysis. The revised core list contains 105 articles and five books. The changes in the field of medical decision making from 1978 to 1981 are reviewed, and key areas of development are identified by co-citation clustering.