A study of structured clinical abstracts and the semantic classification of sentences

Grace Y. Chung; Enrico Coiera

A study of structured clinical abstracts and the semantic classification of sentences

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

This paper describes experiments in classifying sentences of medical abstracts into a number of semantic classes given by section headings in structured abstracts. Using conditional random fields, we obtain -scores ranging from 0.72 to 0.97. By using a small set of sentences that appear under the PAR-TICPANTS heading, we demonstrate that it is possible to recognize sentences that describe population characteristics of a study. We present a detailed study of the structure of abstracts of randomized clinical trials, and examine how sentences labeled under PARTICIPANTS could be used to summarize the population group.

Original language	English
Title of host publication	BioNLP '07 Proceedings of the Workshop on BioNLP 2007
Subtitle of host publication	Biological, Translational, and Clinical Language Processing
Place of Publication	Stroudsburg, PA, USA
Publisher	Association for Computational Linguistics (ACL)
Pages	121-128
Number of pages	8
Publication status	Published - 2007
Externally published	Yes
Event	ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007 - Prague, Czech Republic Duration: 29 Jun 2007 → …

Conference

Conference	ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007
Country/Territory	Czech Republic
City	Prague
Period	29/06/07 → …

Cite this

@inproceedings{c30de55f059e49c4aa1307fd01887998,

title = "A study of structured clinical abstracts and the semantic classification of sentences",

abstract = "This paper describes experiments in classifying sentences of medical abstracts into a number of semantic classes given by section headings in structured abstracts. Using conditional random fields, we obtain -scores ranging from 0.72 to 0.97. By using a small set of sentences that appear under the PAR-TICPANTS heading, we demonstrate that it is possible to recognize sentences that describe population characteristics of a study. We present a detailed study of the structure of abstracts of randomized clinical trials, and examine how sentences labeled under PARTICIPANTS could be used to summarize the population group.",

author = "Chung, \{Grace Y.\} and Enrico Coiera",

year = "2007",

language = "English",

pages = "121--128",

booktitle = "BioNLP '07 Proceedings of the Workshop on BioNLP 2007",

publisher = "Association for Computational Linguistics (ACL)",

note = "ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007 ; Conference date: 29-06-2007",

}

Chung, GY & Coiera, E 2007, A study of structured clinical abstracts and the semantic classification of sentences. in BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing. Association for Computational Linguistics (ACL), Stroudsburg, PA, USA, pp. 121-128, ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007, Prague, Czech Republic, 29/06/07.

A study of structured clinical abstracts and the semantic classification of sentences. / Chung, Grace Y.; Coiera, Enrico.
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL), 2007. p. 121-128.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

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AU - Chung, Grace Y.

AU - Coiera, Enrico

PY - 2007

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N2 - This paper describes experiments in classifying sentences of medical abstracts into a number of semantic classes given by section headings in structured abstracts. Using conditional random fields, we obtain -scores ranging from 0.72 to 0.97. By using a small set of sentences that appear under the PAR-TICPANTS heading, we demonstrate that it is possible to recognize sentences that describe population characteristics of a study. We present a detailed study of the structure of abstracts of randomized clinical trials, and examine how sentences labeled under PARTICIPANTS could be used to summarize the population group.

AB - This paper describes experiments in classifying sentences of medical abstracts into a number of semantic classes given by section headings in structured abstracts. Using conditional random fields, we obtain -scores ranging from 0.72 to 0.97. By using a small set of sentences that appear under the PAR-TICPANTS heading, we demonstrate that it is possible to recognize sentences that describe population characteristics of a study. We present a detailed study of the structure of abstracts of randomized clinical trials, and examine how sentences labeled under PARTICIPANTS could be used to summarize the population group.

UR - https://www.scopus.com/pages/publications/84893401217

UR - http://purl.org/au-research/grants/arc/DP0666600

M3 - Conference proceeding contribution

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EP - 128

BT - BioNLP '07 Proceedings of the Workshop on BioNLP 2007

PB - Association for Computational Linguistics (ACL)

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A study of structured clinical abstracts and the semantic classification of sentences

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