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A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries

Yang, Hui, Spasic, Irena, Keane, John A. and Nenadic, Goran 2009. A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries. Journal of The American Medical Informatics Association 16 (4) , pp. 596-600. 10.1197/jamia.M3096

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Abstract

The authors present a system developed for the Challenge in Natural Language Processing for Clinical Dataâ

Item Type: Article
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: Mcisb; Spasic
Publisher: BMJ Journals
ISSN: 1527-974X
Last Modified: 04 Jun 2017 01:56
URI: http://orca.cf.ac.uk/id/eprint/6210

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Cited 20 times in Google Scholar. View in Google Scholar

Cited 32 times in Scopus. View in Scopus. Powered By Scopus® Data

Cited 10 times in Web of Science. View in Web of Science.

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