Dynamic Surveillance of the Cardiovascular Risk and Identification of Treatment Responders in Type 2 Diabetes Using A Machine Learning-Based Model.

Huang Q, Zou X, Boyko EJ, Lian Z, Zhou X, Han X, Ji L.

Open source

DOI
10.1093/eurjpc/zwag196
Published
2026-04-09
Container
Eur J Prev Cardiol
Publisher
Not recorded
Open access
no

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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

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