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

Development and Evaluation of Research Methods, Instruments and Tools (617) Pilot studies (ehealth) (246) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (904) Data Science (297) Epidemiology (171) Demographics of Users, Social & Digital Divide (821) Ethics, Privacy, and Legal Issues (537)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60878, first published .
Population Characteristics in Justice Health Research Based on PubMed Abstracts From 1963 to 2023: Text Mining Study

Population Characteristics in Justice Health Research Based on PubMed Abstracts From 1963 to 2023: Text Mining Study

Population Characteristics in Justice Health Research Based on PubMed Abstracts From 1963 to 2023: Text Mining Study

Authors of this article:

Wilson Lukmanjaya1 Author Orcid Image ;   Tony Butler1 Author Orcid Image ;   Patricia Taflan1 Author Orcid Image ;   Paul Simpson1 Author Orcid Image ;   Natasha Ginnivan1 Author Orcid Image ;   Iain Buchan2 Author Orcid Image ;   Goran Nenadic3 Author Orcid Image ;   George Karystianis1 Author Orcid Image
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Journals

  1. Wei L, Lu J. Parsing Korean Classical Literature by Integrating Text Mining and Semantic Analysis. Applied Mathematics and Nonlinear Sciences 2025;10(1) View