Miller, R. J. H., Hauser, M. T., Sharir, T., Einstein, A. J., Fish, M. B., Ruddy, T. D., Kaufmann, P. A., Sinusas, A. J., Miller, E. J., Bateman, T. M., Dorbala, S., Di Carli, M., Huang, C., Liang, J. X., Han, D., Dey, D., Berman, D. S., & Slomka, P. J. (2022). Machine learning to predict abnormal myocardial perfusion from pre-test features. Journal of Nuclear Cardiology, 29(5), 2393–2403. https://doi.org/10.1007/s12350-022-03012-6
Subjects:
Myocardial Perfusion Imaging
(MeSH)
Publication Type:
Article
Unique ID:
10.1007/s12350-022-03012-6
PMID:
Journal:
Publication Date:
Data Source:
Scopus