Characterizing potential subgroups and predictive factors of cancer-related fatigue among breast cancer patients through latent profile analysis and machine learning algorithms
- DOI
- 10.1007/s00520-026-11417-z
- Published
- 2026-10-29
- Container
- Supportive Care in Cancer
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s00520-026-11417-z,
title = {Characterizing potential subgroups and predictive factors of cancer-related fatigue among breast cancer patients through latent profile analysis and machine learning algorithms},
author = {Jiashi Zheng and Xiaofang Zhao and Yanhe Cui and Bingyu Liu and Zezu Chen and Xiaomei Lu and Xiaoshi Yang},
year = {2026},
journal = {Supportive Care in Cancer},
doi = {10.1007/s00520-026-11417-z},
url = {https://doi.org/10.1007/s00520-026-11417-z}
}RIS
TY - JOUR TI - Characterizing potential subgroups and predictive factors of cancer-related fatigue among breast cancer patients through latent profile analysis and machine learning algorithms AU - Jiashi Zheng AU - Xiaofang Zhao AU - Yanhe Cui AU - Bingyu Liu AU - Zezu Chen AU - Xiaomei Lu AU - Xiaoshi Yang PY - 2026 JO - Supportive Care in Cancer DO - 10.1007/s00520-026-11417-z UR - https://doi.org/10.1007/s00520-026-11417-z ER -
APA
Zheng, J., Zhao, X., Cui, Y., Liu, B., Chen, Z., Lu, X., & Yang, X. (2026). Characterizing potential subgroups and predictive factors of cancer-related fatigue among breast cancer patients through latent profile analysis and machine learning algorithms. Supportive Care in Cancer. https://doi.org/10.1007/s00520-026-11417-z
Source records
- crossref · retrieved 2026-11-10T12:48:28.191Z