ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2017
Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation.
Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed.
- [Nuclear medicine-necessity and opportunities in modern cardiology].Innere Medizin (Heidelberg, Germany) · 2026Review
- Image Synthesis in Nuclear Medicine Imaging with Deep Learning: A Review.Sensors (Basel, Switzerland) · 2024Review
- A novel algorithm developed using machine learning and a J-ACCESS database can estimate defect scores from myocardial perfusion single-photon emission tomography images.Annals of nuclear medicine · 2024Article
- Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review.Applied bionics and biomechanics · 2024Article
- Artificial Intelligence Empowered Nuclear Medicine and Molecular Imaging in Cardiology: A State-of-the-Art Review.Phenomics (Cham, Switzerland) · 2023Review
- 2022 Artificial intelligence primer for the nuclear cardiologist.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Review
- Preparing for the Artificial Intelligence Revolution in Nuclear Cardiology.Nuclear medicine and molecular imaging · 2023Review
- QCard-NM: Developing a semiautomatic segmentation method for quantitative analysis of the right ventricle in non-gated myocardial perfusion SPECT imaging.EJNMMI physics · 2023Article
- A method using deep learning to discover new predictors from left-ventricular mechanical dyssynchrony for CRT response.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Development of an image classification pipeline for atherosclerotic plaques assessment using supervised machine learning.BMC bioinformatics · 2022Article
- Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation.European journal of nuclear medicine and molecular imaging · 2022Review
- Clinical Deployment of Explainable Artificial Intelligence of SPECT for Diagnosis of Coronary Artery Disease.JACC. Cardiovascular imaging · 2022Article
- Artificial Intelligence and Cardiovascular Risk Prediction: All That Glitters is not Gold.European cardiology · 2022Review
- Artificial intelligence in nuclear cardiology: Preparing for the fifth industrial revolution.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021Article
- A review of the application of machine learning in molecular imaging.Annals of translational medicine · 2021Review
- Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT.European journal of nuclear medicine and molecular imaging · 2021Article
- Machine Learning Adds to Clinical and CAC Assessments in Predicting 10-Year CHD and CVD Deaths.JACC. Cardiovascular imaging · 2021Article
- Evaluating the severity of aortic coarctation in infants using anatomic features measured on CTA.European radiology · 2021Article
- Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021Review
- Artificial Intelligence Based Multimodality Imaging: A New Frontier in Coronary Artery Disease Management.Frontiers in cardiovascular medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Precise definition of the mitral valve plane (VP) during segmentation of the left ventricle for SPECT myocardial perfusion imaging (MPI) quantification often requires manual adjustment, which affects the quantification of perfusion. We developed a machine learning approach using support vector machines (SVM) for automatic VP placement.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.