TY - GEN
T1 - A web-based medical text simplification tool
AU - Kauchak, David
AU - Leroy, Gondy
N1 - Funding Information:
Research reported in this paper was supported by the National Library of Medicine of the National Institutes of Health under Award Number R01LM011975. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2020 IEEE Computer Society. All rights reserved.
PY - 2020
Y1 - 2020
N2 - With the increasing demand for improved health literacy, better tools are needed to produce personalized health information efficiently that is readable and understandable by the patient. In this paper, we introduce a web-based text simplification tool that helps content-producers simplify existing text materials to make them more broadly accessible. The tool uses features that provide concrete suggestions and all features have been shown individually to improve the understandability of text in previous research. We provide an overview of the tool along with a quantitative analysis of the impact on medical texts. On a medical corpus, the tool provides good coverage with suggestions on over a third of the words and over a third of the sentences. These suggestions are over 40% accurate, though the accuracy varies by text source.
AB - With the increasing demand for improved health literacy, better tools are needed to produce personalized health information efficiently that is readable and understandable by the patient. In this paper, we introduce a web-based text simplification tool that helps content-producers simplify existing text materials to make them more broadly accessible. The tool uses features that provide concrete suggestions and all features have been shown individually to improve the understandability of text in previous research. We provide an overview of the tool along with a quantitative analysis of the impact on medical texts. On a medical corpus, the tool provides good coverage with suggestions on over a third of the words and over a third of the sentences. These suggestions are over 40% accurate, though the accuracy varies by text source.
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M3 - Conference contribution
AN - SCOPUS:85108162242
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 3749
EP - 3757
BT - Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
A2 - Bui, Tung X.
PB - IEEE Computer Society
T2 - 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
Y2 - 7 January 2020 through 10 January 2020
ER -