Developing a Simple Non–Laboratory-Based Machine Learning Tool for Prediabetes Screening in a Target Population: A Proof-of-Concept Study
A machine learning screening tool using age and waist circumference was developed with promising results. Its simplicity, by only requiring two non-laboratory features, allows for easy implementation. However, to verify the model's generalizability and external validity, it needs to be evaluated using additional data.
Authors
- Morten Hasselstrøm Jensen (ORCID: https://orcid.org/0000-0002-6649-8644)
- Thomas Kronborg (ORCID: https://orcid.org/0000-0002-2693-0527)
- Tanja Fredensborg Holm (ORCID: https://orcid.org/0009-0007-1725-5922)
- Stine Hangaard (ORCID: https://orcid.org/0000-0003-0395-3563)
Institutions
- Steno Diabetes Centers (DK)
- Novo Nordisk (Denmark) (DK)
- Steno Diabetes Center North Jutland (DK)
- Aalborg University (DK)
Publication Details
- Journal
- Journal of Diabetes Science and Technology
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1177/19322968251376380
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00