Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2022 May 18;289(1975):20212721. doi: 10.1098/rspb.2021.2721

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© 2022 The Authors.

Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

PMC Copyright notice

Figure 1. — Publication trends indicating an earlier adoption, and greater (a) absolute number and (b) proportion of papers involving text mining in biomedical publications compared to ecology and evolutionary biology. Data were from two Web of Science (WOS) searches: one with ‘*medic*’ and the other with ‘ecology’ OR ‘evolutionary biology’ OR ‘biodiversity’ in the Topic field, plus ‘text mining’ OR ‘Natural Language Processing’ OR ‘NLP’ in All Fields for each search. A total of 5262 biomedical papers and 120 ecology/evolutionary biology papers mentioning text mining or NLP were identified out of a total 2 355 632 biomedical and 354 798 ecology/evolution papers. Searches were conducted on 10 September 2021 via the University of Toronto subscription. Note that variation in WOS search results varies owing to institutional subscriptions [10]. Search results were subset to the years 1990–2020 inclusive. Data and R code to reproduce the figure, and .bib files with citation information for the returned articles can be accessed at https://github.com/maxfarrell/textmining_trends. (Online version in colour.)