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

Innovative Methods in Public Health and Surveillance (336) Quality/Credibility of eHealth Information and Trust Issues (544) Infodemiology and Infoveillance (1369) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (159) Pharmacovigilance (138)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53086, first published .
Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

Authors of this article:

Amir Reza Ashraf1 Author Orcid Image ;   Tim Ken Mackey2, 3, 4 Author Orcid Image ;   András Fittler1 Author Orcid Image
Article Authors Cited by (3) Tweetations (6) Metrics

Journals

  1. Deiner M, Honcharov V, Li J, Mackey T, Porco T, Sarkar U. Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study. JMIR Infodemiology 2024;4:e59641 View
  2. Ashraf A, Mackey T, Vida R, Kulcsár G, Schmidt J, Balázs O, Domián B, Li J, Csákó I, Fittler A. Multifactor Quality and Safety Analysis of Semaglutide Products Sold by Online Sellers Without a Prescription: Market Surveillance, Content Analysis, and Product Purchase Evaluation Study. Journal of Medical Internet Research 2024;26:e65440 View

Books/Policy Documents

  1. Wan S. Encyclopedia of Libraries, Librarianship, and Information Science. View