Machine-Learning-Based Diabetes Prediction Using Multisensor Data-Reference-Cited by-同舟云学术

Machine-Learning-Based Diabetes Prediction Using Multisensor Data

Published:2023-11-15 Issue:22 Volume:23 Page:28370-28377
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Site Aditi¹^ORCID,Nurmi Jari¹^ORCID,Lohan Elena Simona¹^ORCID

Affiliation:

1. Electrical Engineering Unit, Tampere University, Tampere, Finland

Funder

Academy of Finland “Secure and Privacy Preserving Healthcare in the Residential Environment with Multimodal Distributed Data and Decentralized AI” and “The Intelligent Society Platform (INSO)”

“INSO” is an Academy-of-Finland-Funded Profiling Action, Operating in Tampere University

AISOLA and SPHERE-DNA NURMI Project Team

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10316685/10268876.pdf?arnumber=10268876

Reference20 articles.

1. The open D1NAMO dataset: A multi-modal dataset for research on non-invasive type 1 diabetes management

2. A Method to Detect Type 1 Diabetes Based on Physical Activity Measurements Using a Mobile Device

3. Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches

4. Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study

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