A large language model-enhanced knowledge graph framework for text-implied public health policy gap screening: digital health executability, behavioral accessibility, and service-support coverage.
- DOI
- 10.3389/fpubh.2026.1937335
- Published
- 2026
- Container
- Frontiers in public health
- 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:10.3389/fpubh.2026.1937335,
title = {A large language model-enhanced knowledge graph framework for text-implied public health policy gap screening: digital health executability, behavioral accessibility, and service-support coverage.},
author = {Wang X and Lu J},
year = {2026},
journal = {Frontiers in public health},
doi = {10.3389/fpubh.2026.1937335},
url = {https://doi.org/10.3389/fpubh.2026.1937335}
}RIS
TY - JOUR TI - A large language model-enhanced knowledge graph framework for text-implied public health policy gap screening: digital health executability, behavioral accessibility, and service-support coverage. AU - Wang X AU - Lu J PY - 2026 JO - Frontiers in public health DO - 10.3389/fpubh.2026.1937335 UR - https://doi.org/10.3389/fpubh.2026.1937335 ER -
APA
X, W., & J, L. (2026). A large language model-enhanced knowledge graph framework for text-implied public health policy gap screening: digital health executability, behavioral accessibility, and service-support coverage.. Frontiers in public health. https://doi.org/10.3389/fpubh.2026.1937335
Source records
- pubmed · retrieved 2026-09-25T19:53:55.752Z