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

Development and Evaluation of Research Methods, Instruments and Tools (511) Scientometrics, Infometrics, and Altmetrics (95)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49721, first published .
Automatic Extraction of Research Themes in Epidemiological Criminology From PubMed Abstracts From 1946 to 2020: Text Mining Study

Automatic Extraction of Research Themes in Epidemiological Criminology From PubMed Abstracts From 1946 to 2020: Text Mining Study

Automatic Extraction of Research Themes in Epidemiological Criminology From PubMed Abstracts From 1946 to 2020: Text Mining Study

Authors of this article:

George Karystianis1 Author Orcid Image ;   Paul Simpson1 Author Orcid Image ;   Wilson Lukmanjaya1 Author Orcid Image ;   Natasha Ginnivan2 Author Orcid Image ;   Goran Nenadic3 Author Orcid Image ;   Iain Buchan4 Author Orcid Image ;   Tony Butler1 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Karystianis G, Lukmanjaya W, Buchan I, Simpson P, Ginnivan N, Nenadic G, Butler T. An analysis of published study designs in PubMed prisoner health abstracts from 1963 to 2023: a text mining study. BMC Medical Research Methodology 2024;24(1) View
  2. Li Y, Luan Z, Liu Y, Liu H, Qi J, Han D. Automated information extraction model enhancing traditional Chinese medicine RCT evidence extraction (Evi-BERT): algorithm development and validation. Frontiers in Artificial Intelligence 2024;7 View
  3. Lukmanjaya W, Butler T, Taflan P, Simpson P, Ginnivan N, Buchan I, Nenadic G, Karystianis G. Population Characteristics in Justice Health Research Based on PubMed Abstracts From 1963 to 2023: Text Mining Study. JMIR Formative Research 2024;8:e60878 View