DETERMINING POST-TEST RISK IN A SAMPLE OF STRESS NUCLEAR MYOCARDIAL PERFUSION IMAGING REPORTS: IMPLICATIONS FOR NATURAL LANGUAGE PROCESSING

Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test ischemic risk. Natural Language Processing (NLP) tools could potentially help estimate this risk, yet it is unknown whether reports contain adequate...

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Bibliographic Details
Published in:Journal of the American College of Cardiology 2018-03, Vol.71 (11), p.A1501-A1501
Main Authors: Levy, Andrew, Shah, Nishant, Reeves, Ruth M., Matheny, Michael, Gobbel, Glenn T., Bradley, Steven
Format: Article
Language:English
Subjects:
Cardiology
Medical imaging
Natural language processing
Perfusion
Online Access:Get full text
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Summary:Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test ischemic risk. Natural Language Processing (NLP) tools could potentially help estimate this risk, yet it is unknown whether reports contain adequate descriptive data to use NLP.
ISSN:0735-1097
1558-3597
DOI:10.1016/S0735-1097(18)32042-4