Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 1997 Nov-Dec;4(6):473-82.
doi: 10.1136/jamia.1997.0040473.

Natural language generation in health care

A J Cawsey  1 , B L Webber, R B Jones
Affiliations
Review

Natural language generation in health care

A J Cawsey et al. J Am Med Inform Assoc. 1997 Nov-Dec.

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.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Example Text From ATTENDING critiquing system.
Figure 2
Figure 2
Critiques Produced by TraumaGEN.
Figure 3
Figure 3
Example Text Planning Operator in Migraine.
Figure 4
Figure 4
Example Text from the PIGLIT system.
Figure 5
Figure 5
Fraction of Progress Note Generated by IVORY.
Figure 6
Figure 6
Example Report from Pen & Pad Reporter.
See this image and copyright information in PMC

References

    1. Friedman C, Johnson SB. Medical text processing: past achievements, future directions. In: Ball M, Morris C (eds). Aspects of the Computer-based Patient Record. New York: Springer-Verlag, 1992; 212-28.
    1. Bateman JA, Hovy EH. An overview of computational text generation In: Butler C (ed). Computers and Texts: An Applied Perspective. London: Basil Blackwell, 1992; 53-74.
    1. Osman LM, Abdulla MI, Beattie JAG, et al. Reducing hospital admission through computer-supported education for asthma patients. British Medical Journal. 1994;308: 568-71. - PMC - PubMed
    1. Campbell MK, DeVellis BM, Strecher VJ, Ammerman AS, DeVellis RF, Sandler RS. Improving dietary behavior: the efficacy of tailored messages in primary care settings. American Journal of Public Health. 1994;84: 783-7. - PMC - PubMed
    1. Strecher VJ, Kreuter M, DenBoer D, Kobrin S, Hospers HJ, Skinner VS. The effects of computer-tailored smoking cessation letters in family practice settings. Journal of Family Practice. 1994;39: 262-270. - PubMed

Publication types

MeSH terms