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Updated: May 7, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Using AI to improve peer review and research integrity in scientific journals
Howard Bauchner1, Frederick Rivara2
1Boston University Chobanian & Avedisian School of Medicine, Visiting Scholar, National University of Singapore.
Abstract:
Peer review is inefficient, biased, and often ineffective. However, its importance in maintaining research integrity, at a time when the public has less faith in science, is clear, since journals are the principal conduit for communicating the results of research to the scientific community and the public. Given that the number of published manuscripts in the biomedical sciences now exceeds 3 million per year it is no longer possible for human editorial and peer review alone to ensure integrity. New approaches are needed, including the use of artificial intelligence (AI) to assist in editorial and peer review.
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