Finding temporal order in discharge summaries.

Finding temporal order in discharge summaries. Research Abstract Details 

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Finding temporal order in discharge summaries. Abstract Text:

Philip Bramsen,Pawan Deshpande,Yoong Keok Lee,Regina Barzilay,

A method for automatic analysis of time-oriented clinical narratives would be of significant practical import for medical decision making, data modeling and biomedical research. This paper proposes a robust corpus-based approach for temporal analysis of medical discharge summaries. We characterize temporal organization of clinical narratives in terms of temporal segments and their ordering. We consider a temporal segment to be a fragment of text that does not exhibit abrupt changes in temporal focus. Our method derives temporal order based on a range of linguistic and contextual features that are integrated in a supervised machine-learning framework. Our learning method achieves 83% F-measure in tempo-ral segmentation, and 78.3% accuracy in inferring pairwise temporal relations.

Finding temporal order in discharge summaries. Publishing Authors By Initials

P Bramsen,P Deshpande,YK Lee,R Barzilay,

For similar natural sciences: time research abstracts see: natural sciences: time research

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Finding temporal order in discharge summaries. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: AMIA ... Annual Symposium proceedings / AMIA Sympo

VOLUME:

Page Numbers: 81-5

Journal Abbreviation:

ISSN: 1559-4076

DAY: 3

MONTH: 12

YEAR: 2006

Finding temporal order in discharge summaries. Information

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LANGUAGE: eng

NlmUniqueID: 101209213

Finding temporal order in discharge summaries. Keywords Mesh Terms:

KEYWORDS: Time

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Grant and Affiliation Information for Finding temporal order in discharge summaries.

AFFILIATION: Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.

Country: United States

AGENCY: United States NLM

GRANT: U54LM008748

ACRONYM: LM

MEDLINETA: AMIA Annu Symp Proc

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