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

Clinical Information and Decision Making (37) Digital Biomarkers and Digital Phenotyping (178) Glucose Tracking and Self-Monitoring of Blood Glucose (152) Artificial Intelligence (1214) Development and Evaluation of Research Methods, Instruments and Tools (439) Diabetes Self-Management (464)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45450, first published .
Machine Learning–Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study

Machine Learning–Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study

Machine Learning–Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study

Authors of this article:

Nicholas Berin Chan1 Author Orcid Image ;   Weizi Li1 Author Orcid Image ;   Theingi Aung2 Author Orcid Image ;   Eghosa Bazuaye2 Author Orcid Image ;   Rosa M Montero3 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

Nicholas Berin Chan   1 , MScR ;   Weizi Li   1 , DPhil ;   Theingi Aung   2 , MBBS, MD ;   Eghosa Bazuaye   2 , MSc ;   Rosa M Montero   3 , MRCP, MBBS, MD

1 Informatics Research Centre, Henley Business School, University of Reading, Reading, United Kingdom

2 Royal Berkshire NHS Foundation Trust, Reading, United Kingdom

3 King's College London, London, United Kingdom

Corresponding Author:

  • Weizi Li, DPhil
  • Informatics Research Centre
  • Henley Business School
  • University of Reading
  • Whiteknights
  • Reading, RG6 6UD
  • United Kingdom
  • Phone: 44 7714021891
  • Email: weizi.li@henley.ac.uk