This paper is in the following e-collection/theme issue:

Adoption and Change Management of eHealth Systems (880) Decision Support for Health Professionals (1513) Electronic Health Records (1296) New Technologies (106) Quality Improvement (290) eHealth Infrastructures (425) Wearable Devices and Sensors (1117) mHealth for Data Collection and Research (1185)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51171, first published .
Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study

Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study

Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study

Authors of this article:

Richard M Yoo1 Author Orcid Image ;   Ben T Viggiano1 Author Orcid Image ;   Krishna N Pundi2 Author Orcid Image ;   Jason A Fries1 Author Orcid Image ;   Aydin Zahedivash3 Author Orcid Image ;   Tanya Podchiyska4 Author Orcid Image ;   Natasha Din4 Author Orcid Image ;   Nigam H Shah1, 5, 6 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Bartusik-Aebisher D, Rogóż K, Aebisher D. Artificial Intelligence and ECG: A New Frontier in Cardiac Diagnostics and Prevention. Biomedicines 2025;13(7):1685 View
  2. Cui Y, Gao J, Zhang J, Li J, Wang Z, Xu S, Zhao J. Machine learning prediction of thrombolysis efficacy using hs-CRP and inflammatory markers in stroke. Medicine 2025;104(43):e45405 View