Leveraging time-series electronic health records with large language models for chronic kidney disease diagnosis in primary care.
- DOI
- 10.1136/bmjhci-2025-101830
- Published
- 2026 Sep 18
- Container
- BMJ health & care informatics
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1136/bmjhci-2025-101830,
title = {Leveraging time-series electronic health records with large language models for chronic kidney disease diagnosis in primary care.},
author = {Wu J and Zheng Y and He Z and Zuo Q and Zhang W and Li P and Luxia Z},
year = {2026},
journal = {BMJ health \& care informatics},
doi = {10.1136/bmjhci-2025-101830},
url = {https://doi.org/10.1136/bmjhci-2025-101830}
}RIS
TY - JOUR TI - Leveraging time-series electronic health records with large language models for chronic kidney disease diagnosis in primary care. AU - Wu J AU - Zheng Y AU - He Z AU - Zuo Q AU - Zhang W AU - Li P AU - Luxia Z PY - 2026 JO - BMJ health & care informatics DO - 10.1136/bmjhci-2025-101830 UR - https://doi.org/10.1136/bmjhci-2025-101830 ER -
APA
J, W., Y, Z., Z, H., Q, Z., W, Z., P, L., & Z, L. (2026). Leveraging time-series electronic health records with large language models for chronic kidney disease diagnosis in primary care.. BMJ health & care informatics. https://doi.org/10.1136/bmjhci-2025-101830
Source records
- pubmed · retrieved 2026-09-25T19:14:59.963Z