Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence—review of evidence and proposition of a roadmap to clinical translation

Qiang Zhang, Anastasia Fotaki, Sona Ghadimi, Yu Wang, Mariya Doneva, Jens Wetzl, Jana G. Delfino, Declan P. O’Regan, Claudia Prieto, Frederick H. Epstein

Open source

DOI
10.1016/j.jocmr.2024.101051
Published
2024
Container
Journal of Cardiovascular Magnetic Resonance
Publisher
Elsevier BV
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1016/j.jocmr.2024.101051,
  title = {Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence—review of evidence and proposition of a roadmap to clinical translation},
  author = {Qiang Zhang and Anastasia Fotaki and Sona Ghadimi and Yu Wang and Mariya Doneva and Jens Wetzl and Jana G. Delfino and Declan P. O’Regan and Claudia Prieto and Frederick H. Epstein},
  year = {2024},
  journal = {Journal of Cardiovascular Magnetic Resonance},
  doi = {10.1016/j.jocmr.2024.101051},
  url = {https://doi.org/10.1016/j.jocmr.2024.101051}
}

RIS

TY  - JOUR
TI  - Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence—review of evidence and proposition of a roadmap to clinical translation
AU  - Qiang Zhang
AU  - Anastasia Fotaki
AU  - Sona Ghadimi
AU  - Yu Wang
AU  - Mariya Doneva
AU  - Jens Wetzl
AU  - Jana G. Delfino
AU  - Declan P. O’Regan
AU  - Claudia Prieto
AU  - Frederick H. Epstein
PY  - 2024
JO  - Journal of Cardiovascular Magnetic Resonance
DO  - 10.1016/j.jocmr.2024.101051
UR  - https://doi.org/10.1016/j.jocmr.2024.101051
ER  - 

APA

Zhang, Q., Fotaki, A., Ghadimi, S., Wang, Y., Doneva, M., Wetzl, J., Delfino, J. G., O’Regan, D. P., Prieto, C., & Epstein, F. H. (2024). Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence—review of evidence and proposition of a roadmap to clinical translation. Journal of Cardiovascular Magnetic Resonance. https://doi.org/10.1016/j.jocmr.2024.101051

Source records