PubMed Health⌕ Search

PubMed · 11933757

Medical informatics: searching for underlying components.

Abstract

OBJECTIVE: To discuss unifying principles that can provide a theory for the diverse aspects of work in medical informatics. If medical informatics is to have academic credibility, it must articulate a clear theory that is distinct from that of computer science or of other related areas of study. RESULTS: The notions of reusable domain antologies and problem-solving methods provide the foundation for current work on second-generation knowledge-based systems. These abstractions are also attractive for defining the core contributions of basic research in informatics. We can understand many central activities within informatics in terms defining, refining, applying, and evaluating domain ontologies and problem-solving methods. CONCLUSION: Construing work in medical informatics in terms of actions involving ontologies and problem-solving methods may move us closer to a theoretical basis for our field.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M A Musen. 2002. Medical informatics: searching for underlying components.. https://pubmed.ncbi.nlm.nih.gov/11933757/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

[Nursing informatics: a new nursing specialty].

It is important to take advantage of advancements in information technology, computers, and the Internet to analyze, manage, and process nursing data to improve the delivery of high quality patient care. Nursing informatics (NI)--which combines nursing, computer, and information sciences--has been recognized as a nursing specialty in the United States since 1992, but is still considered a very new field in Taiwan. The authors introduce the concept by offering a definition of NI and giving descriptions of NI practices, education, and professional groups. The goal is to provide Taiwanese nurses with an informative overview of this specialty.

Information Science↗

A corpus driven approach applying the "frame semantic" method for modeling functional status terminology.

In an effort to unearth semantic models that could prove fruitful to functional-status terminology development we applied the "frame semantic" method, derived from the linguistic theory of thematic roles currently exemplified in the Berkeley "FrameNet" Project. Full descriptive sentences with functional-status conceptual meaning were derived from structured content within a corpus of questionnaire assessment instruments commonly used in clinical practice for functional-status assessment. Syntactic components in those sentences were delineated through manual annotation and mark-up. The annotated syntactic constituents were tagged as frame elements according to their semantic role within the context of the derived functional-status expression. Through this process generalizable "semantic frames" were elaborated with recurring "frame elements". The "frame semantic" method as an approach to rendering semantic models for functional-status terminology development and its use as a basis for machine recognition of functional status data in clinical narratives are discussed.

Information Science↗

Logical support for terminological modeling.

Terminological modeling, in particular in medical domains, is difficult and has enjoyed growing attention over the recent past. In practice, logical reasoning can play a fundamental role to support the modeling process. Nevertheless, the development of the logical tools is usually driven by computational or theoretical criteria rather than by the direct needs of a modeler. In this paper we attempt to shift this balance and discuss a number of logical reasoning services to support the modeler of a (medical) terminology to construct a formally sound, complete and concise terminology. This modeling support is logical as it is based on reasoning services with respect to formally defined semantics. Practical results of this systematic discussion are formal definitions of several new reasoning tasks.

Information Science↗