An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading.
- DOI
- 10.1016/j.jcmg.2024.06.011
- Published
- 2025 Jan
- Container
- JACC. Cardiovascular imaging
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jcmg.2024.06.011,
title = {An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading.},
author = {Sadeghpour A and Jiang Z and Hummel YM and Frost M and Lam CSP and Shah SJ and Lund LH and Stone GW and Swaminathan M and Weissman NJ and Asch FM},
year = {2025},
journal = {JACC. Cardiovascular imaging},
doi = {10.1016/j.jcmg.2024.06.011},
url = {https://doi.org/10.1016/j.jcmg.2024.06.011}
}RIS
TY - JOUR TI - An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading. AU - Sadeghpour A AU - Jiang Z AU - Hummel YM AU - Frost M AU - Lam CSP AU - Shah SJ AU - Lund LH AU - Stone GW AU - Swaminathan M AU - Weissman NJ AU - Asch FM PY - 2025 JO - JACC. Cardiovascular imaging DO - 10.1016/j.jcmg.2024.06.011 UR - https://doi.org/10.1016/j.jcmg.2024.06.011 ER -
APA
A, S., Z, J., YM, H., M, F., CSP, L., SJ, S., LH, L., GW, S., M, S., NJ, W., & FM, A. (2025). An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading.. JACC. Cardiovascular imaging. https://doi.org/10.1016/j.jcmg.2024.06.011
Source records
- pubmed · retrieved 2026-09-25T12:13:15.462Z