Literature DB >> 10566441

Identifying patient subgroups with simple Bayes'.

J M Aronis1, G F Cooper, M Kayaalp, B G Buchanan.   

Abstract

Medical records can form the basis of retrospective studies, be used to evaluate hospital practices and guidelines, and provide examples for teaching medicine. Each of these tasks presumes the ability to accurately identify patient subgroups. We describe a method for selecting patient subgroups based on the text of their medical records and demonstrate its effectiveness. We also describe a modification of the basic system that does not assume the existence of a preclassified training set, and illustrate its effectiveness in one retrieval task.

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Year:  1999        PMID: 10566441      PMCID: PMC2232601     

Source DB:  PubMed          Journal:  Proc AMIA Symp        ISSN: 1531-605X


  3 in total

1.  Evaluation of negation phrases in narrative clinical reports.

Authors:  W W Chapman; W Bridewell; P Hanbury; G F Cooper; B G Buchanan
Journal:  Proc AMIA Symp       Date:  2001

2.  Creating a text classifier to detect radiology reports describing mediastinal findings associated with inhalational anthrax and other disorders.

Authors:  Wendy Webber Chapman; Gregory F Cooper; Paul Hanbury; Brian E Chapman; Lee H Harrison; Michael M Wagner
Journal:  J Am Med Inform Assoc       Date:  2003-06-04       Impact factor: 4.497

3.  Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm.

Authors:  Brian E Chapman; Sean Lee; Hyunseok Peter Kang; Wendy W Chapman
Journal:  J Biomed Inform       Date:  2011-04-01       Impact factor: 6.317

  3 in total

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