This paper is in the following e-collection/theme issue:

Clinical Cancer Research (121) Digital Health Meta-Research and Bibliographic Studies (63) Nephrology/Renal Disorders (103) New Methods (1146) Machine Learning (2134) Innovations and Technology in Cancer Research (44)

Published on in Vol 12 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78797, first published .
Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review

Authors of this article:

Javier De La Hoz-M1 Author Orcid Image ;   Karime Montes-Escobar2, 3 Author Orcid Image ;   Carlos Alfredo Salas-Macias4 Author Orcid Image ;   Martha Fors5 Author Orcid Image ;   Santiago J Ballaz6 Author Orcid Image
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