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

Epidemiology (161) Scientometrics, Infometrics, and Altmetrics (95)

Published on in Vol 11, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42891, first published .
An Analysis of PubMed Abstracts From 1946 to 2021 to Identify Organizational Affiliations in Epidemiological Criminology: Descriptive Study

An Analysis of PubMed Abstracts From 1946 to 2021 to Identify Organizational Affiliations in Epidemiological Criminology: Descriptive Study

An Analysis of PubMed Abstracts From 1946 to 2021 to Identify Organizational Affiliations in Epidemiological Criminology: Descriptive Study

Authors of this article:

George Karystianis1 Author Orcid Image ;   Wilson Lukmanjaya2 Author Orcid Image ;   Paul Simpson1 Author Orcid Image ;   Peter Schofield3 Author Orcid Image ;   Natasha Ginnivan4 Author Orcid Image ;   Goran Nenadic5 Author Orcid Image ;   Marina van Leeuwen6 Author Orcid Image ;   Iain Buchan7 Author Orcid Image ;   Tony Butler1 Author Orcid Image
Article Authors Cited by (3) Tweetations (10) Metrics

Journals

  1. Karystianis G, Simpson P, Lukmanjaya W, Ginnivan N, Nenadic G, Buchan I, Butler T. Automatic Extraction of Research Themes in Epidemiological Criminology From PubMed Abstracts From 1946 to 2020: Text Mining Study. JMIR Formative Research 2023;7:e49721 View
  2. 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
  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