Cited by 75Cardiac Imaging and DiagnosticsRadiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and Education

Evaluation of a Deep Learning–Based Automated CT Coronary Artery Calcium Scoring Algorithm

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Martin, Simon S., van Assen, Marly, Rapaka, Saikiran, Hudson, H. Todd, Fischer, Andreas M., Varga-Szemes, Akos, Sahbaee, Pooyan, Schwemmer, Chris +5 more·2020·JACC: Cardiovascular Imaging

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Crossref · 10.1016/j.jcmg.2019.09.015

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  • Other studies that investigated deep learning algorithms for automated coronary calcium quantification used smaller cohorts or proprietary technologies.

    “Although other studies have investigated deep learning algorithms for automated coronary calcium quantification34–42, they used smaller cohorts or proprietary technologies.”

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Authors
Martin, S. S., van Assen, M., Rapaka, S., Hudson, H. T., Fischer, A. M., Varga-Szemes, A., Sahbaee, P., Schwemmer, C., Gulsun, M. A., Cimen, S., Sharma, P., Vogl, T. J., & Schoepf, U. J.
Affiliations
Medical University of South Carolina (US)
Corresponding author
Schoepf, U. Joseph
Venue
JACC: Cardiovascular Imaging
Publisher
Elsevier BV
Published
2020-02
Volume
13
Issue
2
Pages
524-526
ISSN
  • 1876-7591 (ISSN-L)
  • 1936-878X
OpenAlex
W2989141122
Cited by
75
References
1
Citations by year
2026: 5 · 2025: 8 · 2024: 11 · 2023: 10 · 2022: 17 · 2021: 16 · 2020: 7 · 2019: 1
FWCI
6.76
Type
journal article
Language
en
Open access
Locations
  • JACC. Cardiovascular imaging (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
coronary artery calcium score, deep learning, coronary CT angiography, coronary artery calcification, computer-aided detection, coronary artery disease
MeSH terms
Computed Tomography Angiography, Deep Learning, Aged, Automation, Coronary Artery Disease, Coronary Vessels, Diagnosis, Computer-Assisted, Electrocardiography, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Radiographic Image Interpretation, Computer-Assisted, Retrospective Studies, Severity of Illness Index, Software, Reproducibility of Results, Coronary Angiography, Cardiac-Gated Imaging Techniques, Vascular Calcification

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