Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Research Briefing
  • Published:

Building foundation models for cardiac MRI

A video-based deep-learning system was trained to understand the spectrum of human cardiovascular disease by the self-supervised method of contrastive learning, using pairs of cardiac MRI scans and their corresponding text reports that are generated as part of routine clinical practice.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Large-scale contrastive training.

References

  1. Moor, M. et al. Foundation models for generalist medical artificial intelligence. Nature 616, 259–265 (2023). A review article that discusses foundation models in medical artificial intelligence.

    Article  CAS  PubMed  Google Scholar 

  2. Zhang, Y., Jiang, H., Miura, Y., Manning, C. D. & Langlotz, C. P. Contrastive learning of medical visual representations from paired images and text. in Proc. Mach. Learn. Res. Vol. 182, 1–24 (PMLR, 2022). A seminal paper on the first successful attempt at asymmetrical contrastive learning for medical imaging.

  3. Shad, R., Cunningham, J. P., Ashley, E. A., Langlotz, C. P. & Hiesinger, W. Designing clinically translatable artificial intelligence systems for high-dimensional medical imaging. Nat. Mach. Intell. 3, 929–935 (2021). A review article that discusses the challenges of deep-learning techniques with multi-dimensional imaging data.

    Article  Google Scholar 

  4. Lipkova, J. et al. Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies. Nat. Med. 28, 575–582 (2022). This paper uses multi-instance learning on pathology slides to achieve clinical-grade diagnostic performance at detecting organ rejection in recipients of heart transplant.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This is a summary of: Shad, R. et al. A generalizable deep learning system for cardiac MRI. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-026-01637-3 (2026).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Building foundation models for cardiac MRI. Nat. Biomed. Eng (2026). https://doi.org/10.1038/s41551-026-01638-2

Download citation

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s41551-026-01638-2

Search

Quick links

Nature Briefing AI and Robotics

Sign up for the Nature Briefing: AI and Robotics newsletter — what matters in AI and robotics research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: AI and Robotics