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

Theme Issue: The New Digital Normal in Health and Medicine (40) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1926) JMIR Theme Issue: COVID-19 Special Issue (2556) Natural Language Processing (923) Public (e)Health, Digital Epidemiology and Public Health Informatics (1022) Vaccination and Immunization in the Digital Age (444)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44461, first published .
Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study

Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study

Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study

Authors of this article:

Lea Lösch1 Author Orcid Image ;   Teun Zuiderent-Jerak1 Author Orcid Image ;   Florian Kunneman2 Author Orcid Image ;   Elena Syurina1 Author Orcid Image ;   Marloes Bongers3 Author Orcid Image ;   Mart L Stein3 Author Orcid Image ;   Michelle Chan2 Author Orcid Image ;   Willemine Willems1 Author Orcid Image ;   Aura Timen1, 3, 4 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Jerfy A, Selden O, Balkrishnan R. The Growing Impact of Natural Language Processing in Healthcare and Public Health. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2024;61 View
  2. Yang M, Luo Y, He T, Diao S, Li H, Zou K, Hazlewood G, Vandvik P, Kawano-Dourado L, Dourado D, Dagsvik K, Zeng X, Zhang W, Zhang L, Zeng L. Application of artificial intelligence to measure and predict patient values and preferences: a scoping review. npj Digital Medicine 2025;8(1) View