Artificial Intelligence in Nuclear Cardiology
Author:
Publisher
Society of Nuclear Medicine
Subject
Radiology, Nuclear Medicine and imaging
Reference17 articles.
1. Impact of Appropriate Use on the Prognostic Value of Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging
2. The significance of automatically measured transient ischemic dilation in identifying severe and extensive coronary artery disease in regadenoson, single-isotope technetium-99m myocardial perfusion SPECT;Golzar;J Nucl Cardiol.,2015
3. Prognostic value of heart rate response during regadenoson stress myocardial perfusion imaging in patients with end stage renal disease;AlJaroudi;J Nucl Cardiol.,2016
4. Prognostic implications of stress modality on mortality risk and cause of death in patients undergoing office-based SPECT myocardial perfusion imaging;Poulin;J Nucl Cardiol.,2016
5. The prognostic value of regadenoson SPECT myocardial perfusion imaging in patients with end-stage renal disease;Doukky;J Nucl Cardiol.,2017
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1. Machine learning in cardiac stress test interpretation: a systematic review;European Heart Journal - Digital Health;2024-04-17
2. Need for objective task‐based evaluation of deep learning‐based denoising methods: A study in the context of myocardial perfusion SPECT;Medical Physics;2023-04-20
3. Quality metrics for single-photon emission computed tomography myocardial perfusion imaging: an ASNC information statement;Journal of Nuclear Cardiology;2023-04
4. The Application of AI System in CHD Diagnosis;2023 International Seminar on Computer Science and Engineering Technology (SCSET);2023-04
5. Deep Learning and Artificial Intelligence: What Does the Cardiologist Really Need to Know?;Circulation: Cardiovascular Imaging;2022-09
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