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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 .
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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

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
  3. Kilfoy A, Hamilton R, Howlett M, Yi B, Zupanec S, Jibb L. Health Care Provider–Delivered Educational Interventions in Pediatric Oncology: A Rapid Scoping Review of Content, Feasibility, Acceptability, and Effectiveness. Journal of Pediatric Hematology/Oncology Nursing 2026;43(3):129 View
  4. Adam G, Davies M, Caputo E, Mai H, Coppola E, Holmer H, Kuhn E, Balk E, Trikalinos T, Ivlev I, Wethington H. Artificial intelligence tools for evidence synthesis in the biomedical field: A living rapid review and evidence map. Research Synthesis Methods 2026:1 View
  5. Nussbaumer-Streit B, Dobrescu A, Sharifan A, Klerings I, Neubauer-Bruckner C, Nowak C, Gartlehner G. LLM-based classifiers can reduce the proportion of records to screen with minimal loss of relevant studies: a case study. Journal of Clinical Epidemiology 2026;200:112517 View