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Machine learning to predict abnormal myocardial perfusion from pre-test features

Published Print: 2022-10

Authors

Miller, Robert J.H.

Hauser, M. Timothy

Sharir, Tali

Einstein, Andrew J.

Fish, Mathews B.

Ruddy, Terrence D.

Kaufmann, Philipp A.

Sinusas, Albert J.

Miller, Edward J.

Bateman, Timothy M.

Dorbala, Sharmila

Di Carli, Marcelo

Huang, Cathleen

Liang, Joanna X.

Han, Donghee

Dey, Damini

Berman, Daniel S.

Slomka, Piotr J.
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Text and Data Mining valid from 2022-10-01

Text and Data Mining valid from 2022-10-01
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This article is maintained by: Elsevier

Article Title: Machine learning to predict abnormal myocardial perfusion from pre-test features

Journal Title: Journal of Nuclear Cardiology

CrossRef DOI link to publisher maintained version: https://doi.org/10.1007/s12350-022-03012-6

Content Type: article

Copyright: Copyright © 2022 American Society of Nuclear Cardiology. Published by ELSEVIER INC. All rights reserved. Published by Mosby, Inc. All rights reserved.

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