Mapping intellectual structure and research hotspots of cancer studies in primary health care: A machine-learning-based analysis.

ABSTRACT: In the contemporary fight against cancer, primary health care (PHC) services hold a significant and critical position within the healthcare system. This study, as one of the most detailed investigations into cancer research in primary care, comprehensively evaluates cancer studies from the perspective of PHC using bibliometric techniques and machine learning. The dataset for the analyses was sourced from the Web of Science (WoS) Core Collection database on March 20, 2024. The Bibliometrix package within the R programming environment, alongside the Biblioshiny application, and VOSViewer software were employed for the bibliometric analyses. In this study, Latent Dirichlet Allocation was utilized as a prominent topic modeling algorithm. The implementation of this technique utilized Python alo

SUBMITTER: Damar M 

PROVIDER: S-EPMC11936571 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature