A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region
- DOI
- 10.1038/s41598-025-24450-5
- Published
- 2025-10-20
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-24450-5,
title = {A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region},
author = {Per Wändell and Axel C. Carlsson and Per Swärd and Julia Eriksson and Johan Ärnlöv and Andreas Rosenblad and Caroline Wachtler and Toralph Ruge},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-24450-5},
url = {https://doi.org/10.1038/s41598-025-24450-5}
}RIS
TY - JOUR TI - A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region AU - Per Wändell AU - Axel C. Carlsson AU - Per Swärd AU - Julia Eriksson AU - Johan Ärnlöv AU - Andreas Rosenblad AU - Caroline Wachtler AU - Toralph Ruge PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-24450-5 UR - https://doi.org/10.1038/s41598-025-24450-5 ER -
APA
Wändell, P., Carlsson, A. C., Swärd, P., Eriksson, J., Ärnlöv, J., Rosenblad, A., Wachtler, C., & Ruge, T. (2025). A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region. Scientific Reports. https://doi.org/10.1038/s41598-025-24450-5
Source records
- crossref · retrieved 2026-11-10T19:55:14.492Z