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Journal of the American Medical Informatics Association 4:473-482 (1997)
© 1997 American Medical Informatics Association

Brief Review

Natural Language Generation in Health Care

Alison J. Cawsey, MSc, PhD, Bonnie L. Webber, PhD and Ray B. Jones, MSc, PhD

Affiliations of the authors: Department of Computing and Electrical Engineering, Heriot-Watt University, Edinburgh, Scotland (AJC); Computing and Information Science Department, University of Pennsylvania, Philadelphia, PA (BLW); Department of Public Health, University of Glasgow, Glasgow, Scotland (RBJ).

Correspondence and reprints: Alison Cawsey, Department of Computing and Electrical Engineering, Heriot-Watt University, Edinburgh EH14 4AS, Scotland. E-mail: alison{at}cee.hw.ac.uk

Abstract Good communication is vital in health care, both among health care professionals, and between health care professionals and their patients. And well-written documents, describing and/or explaining the information in structured databases may be easier to comprehend, more edifying, and even more convincing than the structured data, even when presented in tabular or graphic form. Documents may be automatically generated from structured data, using techniques from the field of natural language generation. These techniques are concerned with how the content, organization and language used in a document can be dynamically selected, depending on the audience and context. They have been used to generate health education materials, explanations and critiques in decision support systems, and medical reports and progress notes.




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Copyright © 1997 by the American Medical Informatics Association.