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Protocol for development of an AI-driven individualized frailty prediction and intervention framework for elderly patients with chronic kidney disease: causal feature learning and knowledge-distillation-based modeling study

Crossref DOI link: https://doi.org/10.1186/s12877-026-07143-0

Published Online: 2026-02-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Chang, Jing

Hu, Jing

Cao, Ying

Jia, Xibin

Wang, Luo

Liu, Bo

Xu, Shaowu

Ji, Qing

Jin, Meiling

Han, Qiuxia

Liang, Yuer

Sun, Qianmei
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (Grant NO.62476181)
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Text and Data Mining valid from 2026-02-12

Version of Record valid from 2026-03-18
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Article History

Received: 21 December 2025

Accepted: 4 February 2026

First Online: 12 February 2026

Declarations

:

: This work has been carried out in accordance with the Declaration of Helsinki (2000) of the World Medical Association. This study was approved by Medical Ethics Committee of Beijing Chaoyang Hospital, Capital Medical University, Beijing, China (No. 2024-science-914), and all participants provided written informed consent.

: Not applicable.

: The authors declare no competing interests.

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