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

Digital Health Reviews (858) Wearable Devices and Sensors (678) Diabetes Self-Management (383) Artificial Intelligence (723) Apps, Mobile, Wearables for Diabetes (248) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1072)

Published on in Vol 24 , No 8 (2022) :August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36010, first published .
Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review

Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review

Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping 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 ;   Javaid Sheikh 1 Author Orcid Image
Article Authors Cited by (3) Tweetations (7) Metrics

Journals

  1. Ahamed B, Arya M, Sangeetha S, Auxilia Osvin N, Erdebilli (B. D. Rouyendegh) B. Diabetes Mellitus Disease Prediction and Type Classification Involving Predictive Modeling Using Machine Learning Techniques and Classifiers. Applied Computational Intelligence and Soft Computing 2022;2022:1 View
  2. Abd-alrazaq A, AlSaad R, Aziz S, Ahmed A, Denecke K, Househ M, Farooq F, Sheikh J. Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review. Journal of Medical Internet Research 2023;25:e42672 View
  3. 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