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

Digital Health Reviews (851) Machine Learning (1053) Artificial Intelligence (711) Wearable Devices and Sensors (676) mHealth for Wellness, Behavior Change and Prevention (2342) Web-based and Mobile Health Interventions (2222) Mobile Health (mhealth) (2007)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40259, first published .
The Effectiveness of Wearable Devices Using Artificial Intelligence for Blood Glucose Level Forecasting or Prediction: Systematic Review

The Effectiveness of Wearable Devices Using Artificial Intelligence for Blood Glucose Level Forecasting or Prediction: Systematic Review

The Effectiveness of Wearable Devices Using Artificial Intelligence for Blood Glucose Level Forecasting or Prediction: Systematic Review

Authors of this article:

Arfan Ahmed 1 Author Orcid Image ;   Sarah Aziz 1 Author Orcid Image ;   Alaa Abd-alrazaq 1 Author Orcid Image ;   Faisal Farooq 2 Author Orcid Image ;   Mowafa Househ 3 Author Orcid Image ;   Javaid Sheikh 1 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Ahmed A, Aziz S, Qidwai U, Abd-Alrazaq A, Sheikh J. Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data. Computer Methods and Programs in Biomedicine Update 2023;3:100094 View