Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review
- DOI
- 10.2196/78797
- Published
- 2026-01-16
- Container
- JMIR Cancer
- Publisher
- JMIR Publications Inc.
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.2196/78797,
title = {Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review},
author = {Javier De La Hoz-M and Karime Montes-Escobar and Carlos Alfredo Salas-Macias and Martha Fors and Santiago J Ballaz},
year = {2026},
journal = {JMIR Cancer},
doi = {10.2196/78797},
url = {https://doi.org/10.2196/78797}
}RIS
TY - JOUR TI - Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review AU - Javier De La Hoz-M AU - Karime Montes-Escobar AU - Carlos Alfredo Salas-Macias AU - Martha Fors AU - Santiago J Ballaz PY - 2026 JO - JMIR Cancer DO - 10.2196/78797 UR - https://doi.org/10.2196/78797 ER -
APA
Hoz-M, J. D. L., Montes-Escobar, K., Salas-Macias, C. A., Fors, M., & Ballaz, S. J. (2026). Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review. JMIR Cancer. https://doi.org/10.2196/78797
Source records
- crossref · retrieved 2026-11-04T11:10:06.132Z