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Deep learning with SPECT accurately predicts major adverse cardiac events

An advanced artificial intelligence technique known as deep learning can predict major adverse cardiac events more accurately than current standard imaging protocols, according to research presented at the Society of Nuclear Medicine and Molecular Imaging 2021 Annual Meeting. Utilizing data from a registry of more than 20,000 patients, researchers developed a novel deep learning network that has the potential to provide patients with an individualized prediction of their annualized risk for adverse events. ....

New York , United States , Tel Aviv , Columbia University , Yale University , Sacred Heart Medical Center , Beer Sheba , Tejas Parekh , Joanna Liang , Piotr Slomka , Los Angeles , Robert Miller , Andrew Einstein , Serge Van Kriekinge , Sharmila Dorbala , Yuka Otaki , Timothy Bateman , Wei Chih Chun , Edward Miller , Ananya Singh , Albert Sinusas , Damini Dey , Daniel Berman , Philipp Kaufmann , Paul Kavanagh , Department Of Radiology ,

ASNC, SNMMI Issue Guide for Using PET Myocardial Blood Flow to Improve Diagnosis of Coronary Artery Disease


ASNC, SNMMI Issue Guide for Using PET Myocardial Blood Flow to Improve Diagnosis of Coronary Artery Disease
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The ability to measure myocardial blood flow (MBF) as part of myocardial perfusion imaging (MPI) is one of the most useful developments in contemporary nuclear cardiology. Now, a new practical primer provides clinicians with clear instruction for using this powerful diagnostic tool to improve patient care.
American Society of Nuclear Cardiology
“This document is a valuable tool for learning the essentials of measuring PET myocardial blood flow, and it will be a helpful resource for practitioners at all levels,” says ASNC President Randall C. Thompson, MD, FASNC. ....

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