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

Artificial Intelligence (2437) Decision Support for Health Professionals (1682) mHealth for Screening (313) Surveillance Systems (524) Quality Improvement (313) Theories, Models, and Frameworks in Human Factors (106) Digital Health Reporting Standards, Quality and Transparency in e-Research (161) Machine Learning (2294) Innovative Methods in Public Health and Surveillance (413) Technology in Scientific Publishing (17) AI for Writing and Research Communication (26) Tools and Software for Metascience and Research Integrity Research (25)

Published on in Vol 27 (2025)

This is a member publication of McMaster University

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69700, first published .
Leveraging AI to Optimize Maintenance of Health Evidence and Offer a One-Stop Shop for Quality-Appraised Evidence Syntheses on the Effectiveness of Public Health Interventions: Quality Improvement Project

Leveraging AI to Optimize Maintenance of Health Evidence and Offer a One-Stop Shop for Quality-Appraised Evidence Syntheses on the Effectiveness of Public Health Interventions: Quality Improvement Project

Leveraging AI to Optimize Maintenance of Health Evidence and Offer a One-Stop Shop for Quality-Appraised Evidence Syntheses on the Effectiveness of Public Health Interventions: Quality Improvement Project

Authors of this article:

Kristin Rogers1 Author Orcid Image ;   Alanna Miller1 Author Orcid Image ;   Ashley Girgis1 Author Orcid Image ;   Emily C Clark1 Author Orcid Image ;   Sarah E Neil-Sztramko1, 2 Author Orcid Image ;   Maureen Dobbins1, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Harasgama S, Pearce H, Appel C, Loftus L, Painter H, Kuhn I, Karpusheff J, Ceesay A, Ford J. Artificial Intelligence Tools for Automating Evidence Synthesis: Scoping Review. Journal of Medical Internet Research 2026;28:e81597 View
  2. Zhou F, Lokker C, Parrish R, Haynes R, Iorio A, Saha A, Afzal M. Fine-Tuning and Benchmarking Transformer Models for Multiclass Classification of Clinical Research Papers: Retrospective Modeling Study. JMIR AI 2026;5:e77311 View