Leveraging AI-enhanced digital health with consumer devices for scalable cardiovascular screening, prediction, and monitoring

Aline F Pedroso; Rohan Khera

doi:10.1038/s44325-025-00071-9

Leveraging AI-enhanced digital health with consumer devices for scalable cardiovascular screening, prediction, and monitoring

NPJ Cardiovasc Health. 2025;2(1):34. doi: 10.1038/s44325-025-00071-9. Epub 2025 Jul 2.

Authors

Aline F Pedroso^{1

2}, Rohan Khera^{1

2

3

4}

Affiliations

¹ Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT USA.
² Cardiovascular Data Science (CarDS) Lab, Yale School of Medicine, New Haven, CT USA.
³ Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT USA.
⁴ Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT USA.

Abstract

Traditional cardiovascular care relies on episodic, resource-intensive evaluations. Consumer wearable and portable devices, combined with artificial intelligence (AI), offer a scalable, low-cost alternative. These devices can enhance care with high-fidelity cardiovascular data captured outside traditional care settings, with AI further increasing their value. This review explores how AI-enhanced digital health tools can transform cardiovascular care, improving early detection, personalized risk assessment, and proactive management, particularly in resource-constrained settings, while bridging gaps in traditional care models.

Keywords: Cardiology; Health care.

Publication types

Review