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

Innovative Methods in Public Health and Surveillance (323) Quality/Credibility of eHealth Information and Trust Issues (516) Infodemiology and Infoveillance (1319) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (152) Pharmacovigilance (132)

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 (2) Tweetations (8) 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

Books/Policy Documents

  1. Wan S. Reference Module in Social Sciences. View