Machine Learning for Multi-Vessel Coronary Artery Disease Prediction on Electrocardiogram Gated Single-Photon Emission Computed Tomography-Reference-Cited by-同舟云学术

Machine Learning for Multi-Vessel Coronary Artery Disease Prediction on Electrocardiogram Gated Single-Photon Emission Computed Tomography

Published:2022 Issue: Volume: Page:
ISSN:2189-3926
Container-title:Annals of Nuclear Cardiology
language:en
Short-container-title:

Author:

Shimizu Masato¹,Kimura Shigeki¹,Fujii Hiroyuki¹,Suzuki Makoto¹,Nishizaki Mitsuhiro²,Sasano Tetsuo³

Affiliation:

1. Department of Cardiology, Yokohama Minami Kyosai Hospital

2. Odawara Cardiovascular Hospital

3. Department of Cardiovascular Medicine, Tokyo Medical and Dental University

Publisher

The Japanese Society of Nuclear Cardiology

Subject

General Medicine

Link

https://www.jstage.jst.go.jp/article/anc/advpub/0/advpub_22-00155/_pdf

Reference31 articles.

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3. 3. Lima RSL, Watson DD, Goode AR, Siadaty MS, Ragosta M, Beller GA, et al. Incremental value of combined perfusion and function over perfusion alone by gated SPECT myocardial perfusion imaging for detection of severe three-vessel coronary artery disease. J Am Coll Cardiol 2003; 42: 64–70.

4. 4. Sabharwal N, Lahiri A. Multi-vessel disease and CZT SPECT. Comparison with coronary angiography. J Nucl Cardiol 2017; 24: 696–7.

5. 5. Driessen RS, Raijmakers PG, Danad I, Stuijfzand WJ, Schumacher SP, Lammertsma AA, et al. Adenosine single-photon emission computed tomography-derived transient ischemic dilatation and ejection fraction reserve fail to predict multivessel coronary artery disease. Nucl Med Commun 2019; 40: 773–4.

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