EDITORIAL Nuclear cardiology reporting: Leaving an impression a a Edwin Wu, MD, and Thomas A. Holly, MD Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL Received May 20, 2018; accepted May 21, 2018 doi:10.1007/s12350-018-1315-7 range from cumbersome to burdensome, and despite the See related article, https://doi.org/10. potential beneﬁts, physicians frequently cite the onerous 1007/s12350-018-1275-y. work necessary to utilize any form of structure within their reports. In this issue of the Journal, Levy et al. explore the The performance and interpretation of myocardial possible use of Natural Language Processing (NLP) to perfusion imaging studies are obviously vital compo- determine ischemic risk assessment from stress nents of the stress testing process. How one reports the myocardial perfusion imaging reports. The authors ﬁndings to the referring doctor and other healthcare propose that NLP could be used to improve physicians’ providers is an all too important, and often neglected, understanding of these results and improve utilization, part of the performance of any diagnostic test. Medical speciﬁcally, proper utilization of cardiac catheterization testing is frequently not binomial (normal/abnormal), and revascularization. However, before NLP automated but rather provides a mixture of current and future car- algorithms can be employed to assist with
Journal of Nuclear Cardiology – Springer Journals
Published: Jun 5, 2018
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