Skip to main content

Thank you for visiting 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.

  • Comment
  • Published:

Integrating blockchain technology with artificial intelligence for cardiovascular medicine

Artificial intelligence (AI) holds promise for cardiovascular medicine but is limited by a lack of large, heterogeneous and granular data sets. Blockchain provides secure interoperability between siloed stakeholders and centralized data sources. We discuss integration of blockchain with AI for data-centric analysis and information flow, its current limitations and potential cardiovascular applications.

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: Integration of AI with blockchain moves patients towards the centre of the health-care process.


  1. Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 25, 44–56 (2019).

    Article  CAS  Google Scholar 

  2. Krittanawong, C. et al. Deep learning for cardiovascular medicine: a practical primer. Eur. Heart J. 40, 2058–2073 (2019).

    Article  Google Scholar 

  3. Minchole, A. & Rodriguez, B. Artificial intelligence for the electrocardiogram. Nat. Med. 25, 22–23 (2019).

    Article  CAS  Google Scholar 

  4. Loring, Z., Mehrotra, S. & Piccini, J. P. Machine learning in ‘big data’: handle with care. Europace 21, 1284–1285 (2019).

    Article  Google Scholar 

  5. Giordanengoa, A. Possible usages of smart contracts (blockchain) in healthcare and why no one is using them. Stud. Health Technol. Inform. 264, 596–600 (2019).

    Google Scholar 

  6. Mamoshina, P. et al. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare. Oncotarget 9, 5665–5690 (2018).

    Article  Google Scholar 

  7. de Denus, S. et al. Spironolactone metabolites in TOPCAT — new insights into regional variation. N. Engl. J. Med. 376, 1690–1692 (2017).

    Article  Google Scholar 

  8. Wiggers, K. PatientSphere uses AI and blockchain to personalize treatment plans. VentureBeat (2018).

  9. Popov, G. The future of artifical intelligence in healthcare! SkyChain (2019).

  10. O’Donoghue, O. et al. Design choices and trade-offs in health care blockchain implementations: systematic review. J. Med. Internet Res. 21, e12426 (2019).

    Article  Google Scholar 

Download references


The NIH has awarded grant funding to A.J.R. (F32HL144101) and S.M.N. (HL83359 and HL103800).

Author information

Authors and Affiliations


Corresponding authors

Correspondence to Chayakrit Krittanawong or Sanjiv M. Narayan.

Ethics declarations

Competing interests

S.M.N. has consulted for Abbott Laboratories and and declares Intellectual Property Rights from University of California Regents and Stanford University. The other authors declare no competing interests.

Additional information




Farasha Labs:


MedStar Health Research Institute:


Open Health Network:

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krittanawong, C., Rogers, A.J., Aydar, M. et al. Integrating blockchain technology with artificial intelligence for cardiovascular medicine. Nat Rev Cardiol 17, 1–3 (2020).

Download citation

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


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