Abstract
Cardiovascular disease remains the leading cause of death and disability worldwide. The convergence of big data and artificial intelligence (AI) is reshaping precision cardiovascular medicine through multimodal integration of electronic health records (EHRs), imaging, omics, and wearable data across the care continuum, enabling predictive, diagnostic, therapeutic, and system-level optimization. However, translation into durable clinical benefit remains constrained by evidentiary gaps, implementation complexity, and fragmented governance architectures.
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Acknowledgements
This work was supported by Major Science and Technology Special Projects for Cancer, Cardiovascular, Respiratory and Metabolic Diseases (2025ZD0547200), and Excellent Young Science and Technology Talent Cultivation Special Project of CACMS (CI2023D006).
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Y.L. and YF.L. conceived this topic and arranged the outlines, revised the review. Q.X., YW.L., and M.Z. researched data for the article. Q.X., M.Z., Y.L., Y.C., X.C., W.W., Y.L., J.J., Y.X., and Y.L. substantially contributed to the discussion of content. Q.X., YW.L., and M.Z. wrote the article. All authors reviewed/edited the manuscript before submission.
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Xu, Q., Li, Y., Zhu, M. et al. Precision cardiovascular medicine with big data and AI. npj Digit. Med. (2026). https://doi.org/10.1038/s41746-026-02538-0
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DOI: https://doi.org/10.1038/s41746-026-02538-0
