R Cornet1, C G Chute2. 1. Ronald Cornet, PhD, Visiting Associate Professor, Linköping University, Assistant Professor, Academisch Medisch Centrum, Medical Informatics, J1b-115, P.O. Box 22700, 1100 DE Amsterdam, The Netherlands, E-Mail: r.cornet@amc.uva.nl. 2. Christopher G Chute, MD DrPH, Bloomberg Distinguished Professor of Health Informatics, Professor of Medicine, Public Health, and Nursing, Chief Research Information Officer, Johns Hopkins Medicine, Johns Hopkins University, Division of General Internal Medicine, 2024 E Monument St, Suite 1-200, Baltimore, MD 21287, USA, E-Mail: chute@jhu.edu.
Abstract
OBJECTIVES: The fields of health terminology, classification, ontology, and related information models have evolved dramatically over the past 25 years. Our objective was to review notable trends, described emerging or enabling technologies, and highlight major terminology systems during the interval. METHODS: We review the progression in health terminology systems informed by our own experiences as part of the community involved in this work, reinforced with literature review and citation. RESULTS: The transformation in size, scope, complexity, and adoption of health terminological systems and information models has been tremendous, on the scale of orders of magnitude. CONCLUSION: The present "big science" era of inference and discovery in biomedicine would not have been possible or scalable absent the growth and maturation of health terminology systems and information models over the past 25 years.
OBJECTIVES: The fields of health terminology, classification, ontology, and related information models have evolved dramatically over the past 25 years. Our objective was to review notable trends, described emerging or enabling technologies, and highlight major terminology systems during the interval. METHODS: We review the progression in health terminology systems informed by our own experiences as part of the community involved in this work, reinforced with literature review and citation. RESULTS: The transformation in size, scope, complexity, and adoption of health terminological systems and information models has been tremendous, on the scale of orders of magnitude. CONCLUSION: The present "big science" era of inference and discovery in biomedicine would not have been possible or scalable absent the growth and maturation of health terminology systems and information models over the past 25 years.
Keywords:
Terminology; classification; information model; ontology
Authors: Jean-Marie Rodrigues; Stefan Schulz; Alan Rector; Kent Spackman; Jane Millar; James Campbell; Bedirhan Ustün; Christopher G Chute; Harold Solbrig; Vincenzo Della Mea; Kristina Brand Persson Journal: Stud Health Technol Inform Date: 2014
Authors: John H Holmes; James Beinlich; Mary R Boland; Kathryn H Bowles; Yong Chen; Tessa S Cook; George Demiris; Michael Draugelis; Laura Fluharty; Peter E Gabriel; Robert Grundmeier; C William Hanson; Daniel S Herman; Blanca E Himes; Rebecca A Hubbard; Charles E Kahn; Dokyoon Kim; Ross Koppel; Qi Long; Nebojsa Mirkovic; Jeffrey S Morris; Danielle L Mowery; Marylyn D Ritchie; Ryan Urbanowicz; Jason H Moore Journal: Methods Inf Med Date: 2021-07-19 Impact factor: 1.800