ArticleComputational and mathematical methods in medicine2021
Comparing the Prognostic Value of Stress Myocardial Perfusion Imaging by Conventional and Cadmium-Zinc Telluride Single-Photon Emission Computed Tomography through a Machine Learning Approach.
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Prognostic value of myocardial perfusion imaging by cadmium zinc telluride single-photon emission computed tomography in patients with suspected or known coronary artery disease: a systematic review and meta-analysis.European journal of nuclear medicine and molecular imaging · 2023Pooled it
- Prognostic Significance of Dynamic CZT Cardiac-Dedicated SPECT-derived Myocardial Flow Reserve in Patients with Suspected or Confirmed Coronary Artery Disease and Normal Myocardial PerfusionCurrent medical imaging · 2026Article
- Evaluation of myocardial perfusion imaging techniques and artificial intelligence (AI) tools in coronary artery disease (CAD) diagnosis through multi-criteria decision-making method.Cardiovascular diagnosis and therapy · 2024Article
- Machine learning for prognostic prediction in coronary artery disease with SPECT data: a systematic review and meta-analysis.EJNMMI research · 2024Review
- Regional myocardial perfusion imaging in predicting vessel-related outcome: interplay between the perfusion results and angiographic findings.European journal of nuclear medicine and molecular imaging · 2022Article
- Interplay between gait and neuropsychiatric symptoms in Parkinson's Disease.European journal of translational myology · 2022Article
Corrections and comments
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Authors and funding
18 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We compared the prognostic value of myocardial perfusion imaging (MPI) by conventional- (C-) single-photon emission computed tomography (SPECT) and cadmium-zinc-telluride- (CZT-) SPECT in a cohort of patients with suspected or known coronary artery disease (CAD) using machine learning (ML) algorithms. A total of 453 consecutive patients underwent stress MPI by both C-SPECT and CZT-SPECT. The outcome was a composite end point of all-cause death, cardiac death, nonfatal myocardial infarction, or coronary revascularization procedures whichever occurred first. ML analysis performed through the implementation of random forest (RF) and
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Registered trials
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