Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Schema for Representing Medical Language Applied to Clinical Radiology

A Schema for Representing Medical Language Applied to Clinical Radiology Abstract Objective: Develop a representational schema for clinical concepts and apply it to the task of encoding radiology reports of the chest. Design: The schema was developed following a manual analysis of sample reports from the domain. The schema has two main components: the Medical Entities Dictionary (MED), which specifies the formal representation of the concepts in the domain and of their structures, and the natural-language processor, which specifies the linguistic expressions of the concepts. The schema was evaluated by applying it to a test set of 7,500 reports. Two-hundred reports from the test set were manually analyzed by a medical expert to determine the accuracy and success rate of the system. Results: 82% of the 7,500 reports that contained relevant clinical information were successfully structured automatically. For the smaller set of 200 reports, 80% were structured successfully with an accuracy rate of 97%. Conclusions: The schema is a formal representation for clinical concepts in radiology reports, and provides domain coverage that is particularly well-suited for natural-language processing of radiology for use in a decision support system. This content is only available as a PDF. Author notes Supported in part by grant R29 LM05397 from the National Library of Medicine, by grant 6-61383 from the Research Foundation of CUNY, by a Unified Medical Language System grant from the National Library of Medicine, and by a development contract with IBM Corporation. American Medical Informatics Association http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Medical Informatics Association Oxford University Press

A Schema for Representing Medical Language Applied to Clinical Radiology

Loading next page...
 
/lp/oxford-university-press/a-schema-for-representing-medical-language-applied-to-clinical-zo00z8evjq

References (0)

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Oxford University Press
Copyright
American Medical Informatics Association
ISSN
1067-5027
eISSN
1527-974X
DOI
10.1136/jamia.1994.95236155
Publisher site
See Article on Publisher Site

Abstract

Abstract Objective: Develop a representational schema for clinical concepts and apply it to the task of encoding radiology reports of the chest. Design: The schema was developed following a manual analysis of sample reports from the domain. The schema has two main components: the Medical Entities Dictionary (MED), which specifies the formal representation of the concepts in the domain and of their structures, and the natural-language processor, which specifies the linguistic expressions of the concepts. The schema was evaluated by applying it to a test set of 7,500 reports. Two-hundred reports from the test set were manually analyzed by a medical expert to determine the accuracy and success rate of the system. Results: 82% of the 7,500 reports that contained relevant clinical information were successfully structured automatically. For the smaller set of 200 reports, 80% were structured successfully with an accuracy rate of 97%. Conclusions: The schema is a formal representation for clinical concepts in radiology reports, and provides domain coverage that is particularly well-suited for natural-language processing of radiology for use in a decision support system. This content is only available as a PDF. Author notes Supported in part by grant R29 LM05397 from the National Library of Medicine, by grant 6-61383 from the Research Foundation of CUNY, by a Unified Medical Language System grant from the National Library of Medicine, and by a development contract with IBM Corporation. American Medical Informatics Association

Journal

Journal of the American Medical Informatics AssociationOxford University Press

Published: May 1, 1994

There are no references for this article.