Open AccessDetermining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: Implications for natural language processing tools
Author(s) -
Andrew Levy,
Nishant Shah,
Michael E. Matheny,
Ruth Reeves,
Glenn T. Gobbel,
Steven M Bradley
Publication year - 2019
Publication title -
journal of nuclear cardiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.791
H-Index - 82
eISSN - 1532-6551
pISSN - 1071-3581
DOI - 10.1007/s12350-018-1275-y
Subject(s) - medicine , stress test , myocardial perfusion imaging , context (archaeology) , test (biology) , stress testing (software) , clarity , sample (material) , stress (linguistics) , risk assessment , natural language processing , radiology , perfusion , linguistics , computer science , programming language , philosophy , computer security , paleontology , biochemistry , chemistry , finance , chromatography , biology , economics
Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test 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.