Interpretable machine learning for multiclass trajectory prediction in cardiovascular-kidney-metabolic syndrome stage: development and external validation
- DOI
- 10.3389/fendo.2026.1907821
- Published
- 2026-09-04
- Container
- Frontiers in Endocrinology
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fendo.2026.1907821,
title = {Interpretable machine learning for multiclass trajectory prediction in cardiovascular-kidney-metabolic syndrome stage: development and external validation},
author = {Tian Zhang and Zhenxu Ning and Yangwei Fan and Zhou Zidong and Jingyi Lei and Shuangxing Du and Shuzhen He},
year = {2026},
journal = {Frontiers in Endocrinology},
doi = {10.3389/fendo.2026.1907821},
url = {https://doi.org/10.3389/fendo.2026.1907821}
}RIS
TY - JOUR TI - Interpretable machine learning for multiclass trajectory prediction in cardiovascular-kidney-metabolic syndrome stage: development and external validation AU - Tian Zhang AU - Zhenxu Ning AU - Yangwei Fan AU - Zhou Zidong AU - Jingyi Lei AU - Shuangxing Du AU - Shuzhen He PY - 2026 JO - Frontiers in Endocrinology DO - 10.3389/fendo.2026.1907821 UR - https://doi.org/10.3389/fendo.2026.1907821 ER -
APA
Zhang, T., Ning, Z., Fan, Y., Zidong, Z., Lei, J., Du, S., & He, S. (2026). Interpretable machine learning for multiclass trajectory prediction in cardiovascular-kidney-metabolic syndrome stage: development and external validation. Frontiers in Endocrinology. https://doi.org/10.3389/fendo.2026.1907821
Source records
- crossref · retrieved 2026-09-26T14:56:38.009Z