Optimising test intervals for individuals with type 2 diabetes: A machine learning approach
We demonstrate the potential to use ML in personalised diabetes management by assisting physicians in categorising patients by testing frequencies. Clinical validation on diverse patient populations is needed to assess the model's performance in real-world settings.
Authors
- Trine Kjær (ORCID: https://orcid.org/0000-0002-9554-374X)
- Sasja Maria Pedersen (ORCID: https://orcid.org/0000-0002-2011-4625)
- Kim Rose Olsen (ORCID: https://orcid.org/0000-0002-0473-4736)
- Nicolai Damslund (ORCID: https://orcid.org/0000-0002-4649-3109)
Institutions
- University of Southern Denmark (DK)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1371/journal.pone.0317722
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 5.88
Funders
- Novo Nordisk
- Novo Nordisk Fonden