Diagnostic accuracy of an artificial neural network compared with statistical quantitation of myocardial perfusion images: a Japanese multicenter study
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Title
Diagnostic accuracy of an artificial neural network compared with statistical quantitation of myocardial perfusion images: a Japanese multicenter study
Authors
Keywords
Artificial intelligence, Diagnostic imaging, Coronary artery disease, Nuclear cardiology, Computer-aided diagnosis
Journal
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
Volume 44, Issue 13, Pages 2280-2289
Publisher
Springer Nature
Online
2017-09-26
DOI
10.1007/s00259-017-3834-x
References
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Related references
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- Diagnostic Performance of Artificial Neural Network for Detecting Ischemia in Myocardial Perfusion Imaging
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- 2014 ESC/EACTS Guidelines on myocardial revascularization
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- (2013) R. Arsanjani et al. JOURNAL OF NUCLEAR MEDICINE
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- (2010) Kenichi Nakajima ANNALS OF NUCLEAR MEDICINE
- An open-source framework of neural networks for diagnosis of coronary artery disease from myocardial perfusion SPECT
- (2010) Levent A. Guner et al. JOURNAL OF NUCLEAR CARDIOLOGY
- The importance of population-specific normal database for quantification of myocardial ischemia: comparison between Japanese 360 and 180-degree databases and a US database
- (2009) Kenichi Nakajima et al. JOURNAL OF NUCLEAR CARDIOLOGY
- Evaluation of a decision support system for interpretation of myocardial perfusion gated SPECT
- (2008) Milan Lomsky et al. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
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