Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging

Williams, M. C., Bednarski, B. P., Pieszko, K., Miller, R. J. H., Kwiecinski, J., Shanbhag, A., Liang, J. X., Huang, C., Sharir, T., Dorbala, S., Di Carli, M. F., Einstein, A. J., Sinusas, A. J., Miller, E. J., Bateman, T. M., Fish, M. B., Ruddy, T. D., Acampa, W., Hauser, M. T., … Slomka, P. J. (2023). Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging. European Journal of Nuclear Medicine and Molecular Imaging, 50(9), 2656–2668. https://doi.org/10.1007/s00259-023-06218-z
Authors:
Michelle C Williams
Bryan P Bednarski
Konrad Pieszko
Robert J H Miller
Jacek Kwiecinski
Aakash Shanbhag
Joanna X Liang
Cathleen Huang
Tali Sharir
Sharmila Dorbala
Marcelo F Di Carli
Andrew J Einstein
Albert J Sinusas
Edward J Miller
Timothy M Bateman
Mathews B Fish
Terrence D Ruddy
Wanda Acampa
M Timothy Hauser
Philipp A Kaufmann
Damini Dey
Daniel S Berman
Piotr J Slomka
Affiliated Authors:
Andrew J Einstein
Author Keywords:
cardiovascular risk
cluster analysis
coronary artery disease
machine learning
spect myocardial perfusion
Publication Type:
Article
Unique ID:
10.1007/s00259-023-06218-z
PMID:
Publication Date:
Data Source:
PubMed

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