Artificial intelligence for disease diagnosis and risk prediction in nuclear cardiology

RJH Miller, C Huang, JX Liang, PJ Slomka - Journal of Nuclear Cardiology, 2022 - Elsevier
Artificial intelligence (AI) techniques have emerged as a highly efficient approach to
accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear …

[HTML][HTML] Visually estimated coronary artery calcium score improves SPECT-MPI risk stratification

C Trpkov, A Savtchenko, Z Liang, P Feng… - IJC Heart & …, 2021 - Elsevier
Aims Computed tomographic attenuation correction (CTAC) scans for single photon
emission computed tomography myocardial perfusion imaging (SPECT-MPI) may reveal …

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

MC Williams, BP Bednarski, K Pieszko… - European Journal of …, 2023 - Springer
Purpose Patients with known coronary artery disease (CAD) comprise a heterogenous
population with varied clinical and imaging characteristics. Unsupervised machine learning …

[HTML][HTML] Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography

RJH Miller, A Killekar, A Shanbhag, B Bednarski… - Nature …, 2024 - nature.com
Chest computed tomography is one of the most common diagnostic tests, with 15 million
scans performed annually in the United States. Coronary calcium can be visualized on these …

Direct risk assessment from myocardial perfusion imaging using explainable deep learning

A Singh, RJH Miller, Y Otaki, P Kavanagh… - Cardiovascular …, 2023 - jacc.org
Background Myocardial perfusion imaging (MPI) is frequently used to provide risk
stratification, but methods to improve the accuracy of these predictions are needed …

[HTML][HTML] Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study

RJH Miller, BP Bednarski, K Pieszko, J Kwiecinski… - …, 2024 - thelancet.com
Background Myocardial perfusion imaging (MPI) is one of the most common cardiac scans
and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk …

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging

A Feher, B Bednarski, RJ Miller… - Journal of Nuclear …, 2024 - Soc Nuclear Med
Heart failure (HF) is a leading cause of morbidity and mortality in the United States and
worldwide, with a high associated economic burden. This study aimed to assess whether …

[HTML][HTML] Spherization indices measured by resting SPECT improve risk stratification in patients with ischemia with non-obstructive coronary artery disease (INOCA)

Y Zhao, Y Hu, Y Li, Y Wang, Y Xiao, L Xu, T Ren, Q Wu… - EJNMMI research, 2024 - Springer
Background The prevalence of ischemia with non-obstructive coronary artery disease
(INOCA) is substantial, but its risk stratification has been suboptimal. Resting SPECT …

[PDF][PDF] Unsupervised learning tocharacterize patients withknown coronary artery disease undergoing myocardial perfusion imaging

AJ Einstein, AJ Sinusas, EJ Miller, TM Bateman… - 2023 - core.ac.uk
Purpose Patients with known coronary artery disease (CAD) comprise a heterogenous
population with varied clinical and imaging characteristics. Unsupervised machine learning …

[HTML][HTML] Nuclear cardiac imaging between implementation and globalization: The key role of integration

A Cuocolo, C Nappi, W Acampa, M Petretta - Journal of Nuclear …, 2021 - Springer
It has now been 5 years since we had the privilege of writing our first annual Editor Page.
Since then, many things have changed in the world of science, from diagnostics and …