Dynamic Surveillance of the Cardiovascular Risk and Identification of Treatment Responders in Type 2 Diabetes Using A Machine Learning-Based Model.
- DOI
- 10.1093/eurjpc/zwag196
- Published
- 2026-04-09
- Container
- Eur J Prev Cardiol
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1093/eurjpc/zwag196,
title = {Dynamic Surveillance of the Cardiovascular Risk and Identification of Treatment Responders in Type 2 Diabetes Using A Machine Learning-Based Model.},
author = {Huang Q and Zou X and Boyko EJ and Lian Z and Zhou X and Han X and Ji L.},
year = {2026},
journal = {Eur J Prev Cardiol},
doi = {10.1093/eurjpc/zwag196},
url = {https://doi.org/10.1093/eurjpc/zwag196}
}RIS
TY - JOUR TI - Dynamic Surveillance of the Cardiovascular Risk and Identification of Treatment Responders in Type 2 Diabetes Using A Machine Learning-Based Model. AU - Huang Q AU - Zou X AU - Boyko EJ AU - Lian Z AU - Zhou X AU - Han X AU - Ji L. PY - 2026 JO - Eur J Prev Cardiol DO - 10.1093/eurjpc/zwag196 UR - https://doi.org/10.1093/eurjpc/zwag196 ER -
APA
Q, H., X, Z., EJ, B., Z, L., X, Z., X, H., & L., J. (2026). Dynamic Surveillance of the Cardiovascular Risk and Identification of Treatment Responders in Type 2 Diabetes Using A Machine Learning-Based Model.. Eur J Prev Cardiol. https://doi.org/10.1093/eurjpc/zwag196
Source records
- europe-pmc · retrieved 2026-09-25T08:42:23.847Z