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CORRECTION article

Front. Clin. Diabetes Healthc., 07 June 2023
Sec. Diabetes Innovative Devices
Volume 4 - 2023 | https://doi.org/10.3389/fcdhc.2023.1227105
This article is part of the Research Topic The Use of Machine Learning Approaches in Clinical Research of Diabetes View all 3 articles

Corrigendum: Automatic inference of hypoglycemia causes in type 1 diabetes: a feasibility study

This article is a correction to:

  1. Automatic inference of hypoglycemia causes in type 1 diabetes: a feasibility study

    1. Read original article
Aleksandr ZaitcevAleksandr Zaitcev1Mohammad R. Eissa*Mohammad R. Eissa1*Zheng HuiZheng Hui1Tim GoodTim Good1Jackie Elliott,Jackie Elliott2,3Mohammed BenaissaMohammed Benaissa1
  • 1Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, United Kingdom
  • 2Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom
  • 3Department of Diabetes and Endocrinology, Sheffield Teaching Hospitals NHS FT, Sheffield, United Kingdom

A Corrigendum on
Automatic inference of hypoglycemia causes in type 1 diabetes: a feasibility study

by Zaitcev A, Eissa MR, Hui Z, Good T, Elliott J and Benaissa M (2023) Front. Clin. Diabetes Healthc. 4:1095859. doi: 10.3389/fcdhc.2023.1095859

In the published article, the supporting funder, University of Sheffield Institutional Open Access Fund was erroneously omitted in the Funding statement as published. Instead of

This study is funded by the National Institute for Health Research (NIHR) [Programme Grants for Applied Research (RP-PG-0514-20013) DAFNEplus]. It should be

This study is funded by the National Institute for Health Research (NIHR) [Programme Grants for Applied Research (RP-PG-0514-20013) DAFNEplus]. This article was also supported by University of Sheffield Institutional Open Access Fund.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: biomedical informatics, classification algorithms, machine learning, medical expert systems, statistical analysis, hypoglycemia, exercise, physical activity

Citation: Zaitcev A, Eissa MR, Hui Z, Good T, Elliott J and Benaissa M (2023) Corrigendum: Automatic inference of hypoglycemia causes in type 1 diabetes: a feasibility study. Front. Clin. Diabetes Healthc. 4:1227105. doi: 10.3389/fcdhc.2023.1227105

Received: 22 May 2023; Accepted: 23 May 2023;
Published: 07 June 2023.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2023 Zaitcev, Eissa, Hui, Good, Elliott and Benaissa. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Mohammad R. Eissa, m.eissa@sheffield.ac.uk

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.