Leveraging Self-Supervised Learning for Non-Invasive Intra-Cardiac Magnetic Resonance Oximetry Assessment.
- DOI
- 10.64898/2026.06.29.26356860
- Published
- 2026 Jul 1
- Container
- medRxiv : the preprint server for health sciences
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.64898/2026.06.29.26356860,
title = {Leveraging Self-Supervised Learning for Non-Invasive Intra-Cardiac Magnetic Resonance Oximetry Assessment.},
author = {Chen J and Pham TH and Zhang P and Varghese J},
year = {2026},
journal = {medRxiv : the preprint server for health sciences},
doi = {10.64898/2026.06.29.26356860},
url = {https://doi.org/10.64898/2026.06.29.26356860}
}RIS
TY - JOUR TI - Leveraging Self-Supervised Learning for Non-Invasive Intra-Cardiac Magnetic Resonance Oximetry Assessment. AU - Chen J AU - Pham TH AU - Zhang P AU - Varghese J PY - 2026 JO - medRxiv : the preprint server for health sciences DO - 10.64898/2026.06.29.26356860 UR - https://doi.org/10.64898/2026.06.29.26356860 ER -
APA
J, C., TH, P., P, Z., & J, V. (2026). Leveraging Self-Supervised Learning for Non-Invasive Intra-Cardiac Magnetic Resonance Oximetry Assessment.. medRxiv : the preprint server for health sciences. https://doi.org/10.64898/2026.06.29.26356860
Source records
- pubmed · retrieved 2026-09-25T20:09:57.997Z