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

Reviews in Medical Informatics (83) Wearable Devices and Sensors (825) Cardiac Risk and Cardiac Risk Calculators (33) Cardiac Self-Management (98) Cardiovascular Disease Prevention (115) Mobile Apps for Cardiology (127) Consumer Health Informatics Innovations (14) New Technologies (67) Machine Learning (1401) mHealth for Wellness, Behavior Change and Prevention (2754)

Published on in Vol 10, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29434, first published .
Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View

Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View

Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View

Authors of this article:

Arman Naseri Jahfari1, 2 Author Orcid Image ;   David Tax1 Author Orcid Image ;   Marcel Reinders1 Author Orcid Image ;   Ivo van der Bilt2 Author Orcid Image
Article Authors Cited by (7) Tweetations (10) Metrics

Arman Naseri Jahfari   1, 2 , MSc ;   David Tax   1 , PhD ;   Marcel Reinders   1 , PhD ;   Ivo van der Bilt   2 , MD, PhD

1 Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, Netherlands

2 Department of Cardiology, Haga Teaching Hospital, The Hague, Netherlands

Corresponding Author:

  • Arman Naseri Jahfari, MSc
  • Pattern Recognition and Bioinformatics
  • Delft University of Technology
  • van Mourik Broekmanweg 6
  • Delft, 2628 XE
  • Netherlands
  • Phone: 31 152786052
  • Email: a.naserijahfari@tudelft.nl