Machine learning and engagement insights for personalized blood glucose management.

Breuer Asher I, Horwitz DL, Manejwala O, Fundoiano-Hershcovitz Y.

Open source

DOI: 10.3389/fdgth.2026.1660815
Published: 2026-02-24
Container: Front Digit Health
Publisher: Not recorded
Open access: yes

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uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.3389/fdgth.2026.1660815,
  title = {Machine learning and engagement insights for personalized blood glucose management.},
  author = {Breuer Asher I and  Horwitz DL and  Manejwala O and  Fundoiano-Hershcovitz Y.},
  year = {2026},
  journal = {Front Digit Health},
  doi = {10.3389/fdgth.2026.1660815},
  url = {https://doi.org/10.3389/fdgth.2026.1660815}
}

RIS

TY  - JOUR
TI  - Machine learning and engagement insights for personalized blood glucose management.
AU  - Breuer Asher I
AU  -  Horwitz DL
AU  -  Manejwala O
AU  -  Fundoiano-Hershcovitz Y.
PY  - 2026
JO  - Front Digit Health
DO  - 10.3389/fdgth.2026.1660815
UR  - https://doi.org/10.3389/fdgth.2026.1660815
ER  -

APA

I, B. A., DL, H., O, M., & Y., F. (2026). Machine learning and engagement insights for personalized blood glucose management.. Front Digit Health. https://doi.org/10.3389/fdgth.2026.1660815

Source records

europe-pmc · retrieved 2026-09-27T02:15:39.570Z
doaj · retrieved 2026-09-27T02:15:39.575Z