PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 10179587

Using the GRAIL language for classification management.

P E Zanstra·E J van der Haring·F Flier·J E Rogers·W D Solomon
View original source ↗Export metadata ↓

Abstract

This paper describes a novel approach in classification management where a formal model of medical semantics is being used for manipulations on existing classification systems. The paper addresses the issue of semi-automatically making specialist classifications that are compatible with the source classification. The examples in this paper are from a limited domain. At the time of the presentation results will be shown of the present modelling work within the GALEN-In-Use project. The model will then contain several thousands of medical procedures from four different classification centres.

Explore related subjects

ClassificationEuropeHumansInternational CooperationNatural Language ProcessingProgramming LanguagesSemanticsVocabulary, ControlledJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

P E Zanstra, E J van der Haring, F Flier, J E Rogers, W D Solomon. 1997. Using the GRAIL language for classification management.. https://pubmed.ncbi.nlm.nih.gov/10179587/

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

KEEP EXPLORING

Related citations

PubMed2002

TreeWiz: interactive exploration of huge trees.

MOTIVATION: The rapidly increasing amount and disparity of biological data requires interpretation at many levels of description. Human judgement and intuition are important because not all data can be automatically and comprehensively analyzed. Visualization of trees and substructures corresponding to certain features are often used to analyze phylogenies or taxonomies. Unfortunately, most existing tools do not cope with the size of current datasets, the required functionality, or both. RESULTS: We introduce a program for visualization of huge trees and also for the interactive exploration of their content. We have developed a range of new schemes which are tailored for biological problems. Users can get an overview, zoom in, filter out data and retrieve details from standard databases such as SWISS-PROT. Furthermore, it is possible to analyze the relationship between chosen leaf sets that are specified by common features on a second level of representation. On a PC (with approximately equal to 512 MB RAM), trees of up to several tens of thousands of leaves can be loaded and both rapidly and interactively explored. We demonstrate the use of this program for the analysis of the SYSTERS data set (which contains hierarchically clustered protein sequences) to which PFAM domains were added as features.

Classification↗
PubMed2002

A theory-based clinical nurse specialist practice exemplar using Neuman's systems model and nursing's taxonomies.

This article illustrates the process of theory-based advanced nursing practice by presenting an exemplar of clinical nurse specialist practice using Neuman's systems model and nursing's taxonomies. A brief explanation of Neuman's systems model is given, and the process of assessment, diagnosis, and planned outcomes/interventions is fully described. A clinical example illustrates the entire process.

Classification↗
PubMed2002

A model of medical error based on a model of disease: interactions between adverse events, failures, and their errors.

This article discusses Rush-Presbyterian-St. Luke's Medical Center's approach to assessing and preventing errors in care and promoting patient safety. The word error is applied to all kinds of events, including adverse occurrences, negligence, and malpractice. Thus confusion exists among those analyzing the causes of adverse events. A patient safety committee standardized the definition of medical error and developed a taxonomy for error as a prelude to efforts at error reduction. It identified three levels or layers that can represent a train of events culminating in an undesired outcome: error, treatment failure, and adverse event. This discussion is offered in the interest of clarifying some of the issues.

Classification↗