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.

  • News & Views
  • Published:

MACHINE LEARNING

Eyeing cardiovascular risk factors

Smoking status, blood pressure, age and other cardiovascular risk factors can be predicted from retinal images by using deep learning.

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

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

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

Fig. 1: Anatomical regions in retinal fundus images associated with predictions from the deep-learning algorithm.

References

  1. Ho, H. et al. Sci. Rep. 7, 41492 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Cheung, C. Y. et al. Stroke 44, 2402–2408 (2013).

    Article  PubMed  Google Scholar 

  3. Yip, W. et al. Sci. Rep. 7, 9374 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Wong, T. Y., Knudtson, M. D., Klein, R., Klein, B. E. & Hubbard, L. D. Am. J. Epidemiol. 159, 819–825 (2004).

    Article  PubMed  Google Scholar 

  5. McGeechan, K. et al. Ann. Intern. Med. 151, 404–413 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Yip, W. et al. Sci. Rep. 6, 27442 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Poplin, R. et al. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-018-0195-0 (2018).

  8. Brynjolfsson, E. & Mcafee, A. What’s driving the machine learning explosion? Harvard Business Review (18 July 2017).

  9. Ting, D. S. W. et al. JAMA 318, 2211–2223 (2017).

    Article  PubMed  Google Scholar 

  10. Gulshan, V. et al. JAMA 316, 2402–2410 (2016).

    Article  PubMed  Google Scholar 

  11. Wong, T. Y. & Bressler, N. M. JAMA 316, 2366–2367 (2016).

    Article  PubMed  Google Scholar 

  12. Lakhani, P. & Sundaram, B. Radiology 284, 574–582 (2017).

    Article  PubMed  Google Scholar 

  13. Ting, D. S. W., Yi, P. H. & Hui, F. Radiology 286, 729–731 (2018).

    Article  PubMed  Google Scholar 

  14. Esteva, A. et al. Nature 542, 115–118 (2017).

    Article  CAS  PubMed  Google Scholar 

  15. Ehteshami Bejnordi, B. et al. JAMA 318, 2199–2210 (2017).

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Daniel Shu Wei Ting or Tien Yin Wong.

Ethics declarations

Competing interests

D.S.W.T. and T.Y.W. are co-developers of a deep-learning system for diabetic retinopathy, glaucoma and age-related macular degeneration.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ting, D.S.W., Wong, T.Y. Eyeing cardiovascular risk factors. Nat Biomed Eng 2, 140–141 (2018). https://doi.org/10.1038/s41551-018-0210-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41551-018-0210-5

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

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