Deep learning approaches to predict late gadolinium enhancement and clinical outcomes in suspected cardiac sarcoidosis.

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Deep learning approaches to predict late gadolinium enhancement and clinical outcomes in suspected cardiac sarcoidosis.

Authors

  • Levi-Dan Azoulay Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Xueyan Mei Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Valentin Fauveau Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Zelong Liu Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Philip Robson Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Sydney Levi Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Ana Devesa Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Maria-Giovanna Trivieri Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai
  • Zahi Fayad Biomedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai

Keywords:

cardiac sarcoidosis, cardiac magnetic resonance, deep learning

Abstract

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References

Trivieri MG, Spagnolo P, Birnie D, et al. Challenges in cardiac and pulmonary sarcoidosis. J Am Coll Cardiol. 2020;76(16):1878-901. doi:10.1016/j.jacc.2020.08.042.

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Mei X, Lee HC, Diao K, et al. Artificial intelligence-enabled rapid diagnosis of patients with COVID-19. Nat Med. 2020;26(8):1224-8. doi:10.1038/s41591-020-0931-3.

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Mei X, Liu Z, Robson PM, et al. RadImageNet: an open radiologic deep learning research dataset for effective transfer learning. Radiol Artif Intell. 2022;4(5):e210315. doi:10.1148/ryai.210315.

Litjens G, Ciompi F, Wolterink JM, et al. State-of-the-art deep learning in cardiovascular image analysis. JACC Cardiovasc Imaging. 2019;12(8):1549-65. doi:10.1016/j.jcmg.2019.06.009.

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How to Cite

1.
Azoulay L-D, Mei X, Fauveau V, Liu Z, Robson P, Levi S, et al. Deep learning approaches to predict late gadolinium enhancement and clinical outcomes in suspected cardiac sarcoidosis. Sarcoidosis Vasc Diffuse Lung Dis [Internet]. [cited 2025 Mar. 9];42(1): 15378. Available from: https://mattioli1885journals.com/index.php/sarcoidosis/article/view/15378

Issue

Vol. 42 No. 1 (2025)

Section

Letter to Editor
DOI: https://doi.org/10.36141/svdld.v42i1.15378

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How to Cite

1.
Azoulay L-D, Mei X, Fauveau V, Liu Z, Robson P, Levi S, et al. Deep learning approaches to predict late gadolinium enhancement and clinical outcomes in suspected cardiac sarcoidosis. Sarcoidosis Vasc Diffuse Lung Dis [Internet]. [cited 2025 Mar. 9];42(1): 15378. Available from: https://mattioli1885journals.com/index.php/sarcoidosis/article/view/15378
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