Using natural language processing to extract carotid stenosis severity from clinical notes to create a nationwide veteran cohort.

Lee KM, Alba PR, Biagetti GM, Gao A, Yin M, Danilov PN, DiNatale T, Perez C, Hartmann K, Shakt GE, Judy RL, Bellomo TR, Pridgen KM, Tsao PS, Balasundaram N, Levin MG, Damrauer SM, Lynch JA

Open source

DOI
10.1016/j.jvsvi.2025.100302
Published
2025 Oct 31
Container
JVS-vascular insights
Publisher
Not recorded
Open access
yes

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Cite this work

BibTeX

@article{allodium:10.1016/j.jvsvi.2025.100302,
  title = {Using natural language processing to extract carotid stenosis severity from clinical notes to create a nationwide veteran cohort.},
  author = {Lee KM and Alba PR and Biagetti GM and Gao A and Yin M and Danilov PN and DiNatale T and Perez C and Hartmann K and Shakt GE and Judy RL and Bellomo TR and Pridgen KM and Tsao PS and Balasundaram N and Levin MG and Damrauer SM and Lynch JA},
  year = {2025},
  journal = {JVS-vascular insights},
  doi = {10.1016/j.jvsvi.2025.100302},
  url = {https://doi.org/10.1016/j.jvsvi.2025.100302}
}

RIS

TY  - JOUR
TI  - Using natural language processing to extract carotid stenosis severity from clinical notes to create a nationwide veteran cohort.
AU  - Lee KM
AU  - Alba PR
AU  - Biagetti GM
AU  - Gao A
AU  - Yin M
AU  - Danilov PN
AU  - DiNatale T
AU  - Perez C
AU  - Hartmann K
AU  - Shakt GE
AU  - Judy RL
AU  - Bellomo TR
AU  - Pridgen KM
AU  - Tsao PS
AU  - Balasundaram N
AU  - Levin MG
AU  - Damrauer SM
AU  - Lynch JA
PY  - 2025
JO  - JVS-vascular insights
DO  - 10.1016/j.jvsvi.2025.100302
UR  - https://doi.org/10.1016/j.jvsvi.2025.100302
ER  - 

APA

KM, L., PR, A., GM, B., A, G., M, Y., PN, D., T, D., C, P., K, H., GE, S., RL, J., TR, B., KM, P., PS, T., N, B., MG, L., SM, D., & JA, L. (2025). Using natural language processing to extract carotid stenosis severity from clinical notes to create a nationwide veteran cohort.. JVS-vascular insights. https://doi.org/10.1016/j.jvsvi.2025.100302

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