Manchester eScholar Services

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In April 2016 Manchester eScholar was replaced by the University of Manchester’s new Research Information Management System, Pure. In the autumn the University’s research outputs will be available to search and browse via a new Research Portal. Until then the University’s full publication record can be accessed via a temporary portal and the old eScholar content is available to search and browse via this archive.

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

Yang, H., Spasic, I., Keane, J., Nenadic, G

Journal of the American Medical Informatics Association. 2009;16(4):596-600.

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Bibliographic metadata

Type of resource:
Content type:
Publication type:
Published date:
ISSN:
Volume:
16
Issue:
4
Start page:
596
End page:
600
Total:
5
Pagination:
596-600
Digital Object Identifier:
10.1197/jamia.M3096
Access state:
Active

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:50690
Created by:
Nenadic, Goran
Created:
12th October, 2009, 11:33:44
Last modified by:
Nenadic, Goran
Last modified:
26th October, 2015, 13:00:22