Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data

Author:

Ahmed ArfanORCID,Aziz Sarah,Qidwai Uvais,Abd-Alrazaq Alaa,Sheikh Javaid

Publisher

Elsevier BV

Subject

Materials Chemistry

Reference42 articles.

1. IDF diabetes atlas;Atlas;Int. Diabetes Federation (9th editio),2019

2. Overview of artificial intelligence-driven wearable devices for diabetes: scoping review;Ahmed;J. Med. Internet Res.,2022

3. A smartphone-based test and predictive models for rapid, non-invasive, and point-of-care monitoring of ocular and cardiovascular complications related to diabetes;Chakravadhanula;Inf. Med. Unlocked,2021

4. A new strategy for the detection of diabetic retinopathy using a smartphone app and machine learning methods embedded on cloud computer;Alves,2020

5. Prabha, A., et al. Non-invasive diabetes mellitus detection system using machine learning techniques. in 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence). 2021. IEEE.

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