• Mapping intellectual structure...

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

Title:
Mapping intellectual structure and research hotspots of cancer studies in primary health care: A machine-learning-based analysis.
Authors:
Damar M; Dokuz Eylul University, İzmir, Türkiye.; Upstream Lab, MAP, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada., Turhan Damar H; Elderly Care Program, Health Services Vocational School, Izmir Democracy University, Izmir, Turkey., Özbiçakci Ş; Dokuz Eylul University, İzmir, Türkiye., Yasli G; Department of Public Health, İzmir Health Directorate, İzmir, Türkiye., Erenay FS; Management Science and Engineering, University of Waterloo, Waterloo, Ontario, Canada., Özdağoğlu G; Dokuz Eylul University, İzmir, Türkiye., Pinto AD; Upstream Lab, MAP, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada.; Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Source:
Medicine [Medicine (Baltimore)] 2025 Mar 21; Vol. 104 (12), pp. e41749.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 2985248R Publication Model: Print Cited Medium: Internet ISSN: 1536-5964 (Electronic) Linking ISSN: 00257974 NLM ISO Abbreviation: Medicine (Baltimore) Subsets: MEDLINE
Imprint Name(s):
Original Publication: Hagerstown, Md : Lippincott Williams & Wilkins
MeSH Terms:
Primary Health Care* , Machine Learning* , Neoplasms*/therapy , Neoplasms*/diagnosis , Biomedical Research*, Humans ; Bibliometrics
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Entry Date(s):
Date Created: 20250324 Date Completed: 20250514 Latest Revision: 20250514
Update Code:
20250515
PubMed Central ID:
PMC11936571
DOI:
10.1097/MD.0000000000041749
PMID:
40128045
Database:
MEDLINE

Weitere Informationen

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 along with the SciKit-Learn and Gensim libraries, ensuring robust model development and evaluation. The 2040 articles were produced by a total of 6705 different authors, 2166 different affiliations, and 75 different countries. Cancer survivors are more vulnerable and need more sensitive health services. The most intensively studied 3 cancer types in the PHC, listed by prevalence, are colorectal cancer, breast cancer, and cervical cancer. Additionally, prominent research topics in PHC include cancer screening, diagnosis, early detection, prevention, education, genetic factors and family history, risk factors, symptoms/signs, preventive medicine, referral and consultation, chronic disease management and health services research for cancer patients, health care disparities, palliative care, and communication with patients in PHC. Family physicians, being the first point of contact with the public, play a crucial role in preventing cancer cases, caring for patients with active cancer diagnoses, supporting cancer survivors in their post-cancer lives, and identifying and referring cancer cases at the earliest stages. However, cancer has many types, each with its own distinct symptoms, as well as similar types to each other. At this point, periodic educational training for doctors on cancer by health authorities, regular publication of cancer-related guidance resources by the central healthcare system, development of integrated decision support tools used by physicians during patient care, and the creation of informative mobile applications for cancer prevention or post-cancer life for patients have been considered highly critical.
(Copyright © 2025 the Author(s). Published by Wolters Kluwer Health, Inc.)

The authors have no funding and conflicts of interest to disclose.