Analysing clinical guidelines' contents with deontic and rhetorical structures

G. (Gersende) Georg; H. (Hugo) Hernault; M. O. (Marc) Cavazza; H. (Helmut) Prendinger; M. (Mitsuru) Ishizuka

doi:10.1007/978-3-642-02976-9_11

Analysing clinical guidelines' contents with deontic and rhetorical structures

G. (Gersende) Georg, H. (Hugo) Hernault, M. O. (Marc) Cavazza, H. (Helmut) Prendinger, M. (Mitsuru) Ishizuka

SCEDT School Executive Team

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

Original language	English
Title of host publication	Lecture notes in computer science
Publisher	Springer
Volume	5651
ISBN (Print)	9783642029752
DOIs	https://doi.org/10.1007/978-3-642-02976-9_11
Publication status	Published - 2009

Bibliographical note

The computerisation of clinical guidelines can greatly benefit from the automatic analysis of their content using Natural Language Processing techniques. Because of the central role played by specific deontic structures, known as recommendations, it is possible to tune the processing step towards the recognition of such expressions, which can be used to structure key sections of the document. In this paper, we extend previous work on the automatic identification of guidelines' recommendations, by showing how Rhetorical Structure Theory can be used to characterise the actual contents of elementary recommendations. The emphasis on causality and time in RST proves a powerful complement to the recognition of deontic structures and supports the identification of relevant knowledge, in particular for the identification of conditional structures, which play an important role for the subsequent analysis of recommendations.

Access to Document

10.1007/978-3-642-02976-9_11

http://hdl.handle.net/10149/91086

Cite this

@inproceedings{a4fe0058888b4de1b091e3f39d31a309,

title = "Analysing clinical guidelines' contents with deontic and rhetorical structures",

author = "Georg, {G. (Gersende)} and Hernault, {H. (Hugo)} and Cavazza, {M. O. (Marc)} and Prendinger, {H. (Helmut)} and Ishizuka, {M. (Mitsuru)}",

note = "The computerisation of clinical guidelines can greatly benefit from the automatic analysis of their content using Natural Language Processing techniques. Because of the central role played by specific deontic structures, known as recommendations, it is possible to tune the processing step towards the recognition of such expressions, which can be used to structure key sections of the document. In this paper, we extend previous work on the automatic identification of guidelines' recommendations, by showing how Rhetorical Structure Theory can be used to characterise the actual contents of elementary recommendations. The emphasis on causality and time in RST proves a powerful complement to the recognition of deontic structures and supports the identification of relevant knowledge, in particular for the identification of conditional structures, which play an important role for the subsequent analysis of recommendations.",

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AU - Georg, G. (Gersende)

AU - Hernault, H. (Hugo)

AU - Cavazza, M. O. (Marc)

AU - Prendinger, H. (Helmut)

AU - Ishizuka, M. (Mitsuru)

N1 - The computerisation of clinical guidelines can greatly benefit from the automatic analysis of their content using Natural Language Processing techniques. Because of the central role played by specific deontic structures, known as recommendations, it is possible to tune the processing step towards the recognition of such expressions, which can be used to structure key sections of the document. In this paper, we extend previous work on the automatic identification of guidelines' recommendations, by showing how Rhetorical Structure Theory can be used to characterise the actual contents of elementary recommendations. The emphasis on causality and time in RST proves a powerful complement to the recognition of deontic structures and supports the identification of relevant knowledge, in particular for the identification of conditional structures, which play an important role for the subsequent analysis of recommendations.

PY - 2009

Y1 - 2009

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DO - 10.1007/978-3-642-02976-9_11

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SN - 9783642029752

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BT - Lecture notes in computer science

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