June 14, 2026European Heart Journal
Artificial Intelligence in Biomedical Scientific Publishing
Key result
Artificial intelligence in biomedical publishing offers opportunities to accelerate knowledge generation but introduces risks requiring transparency, provenance, and enforceable human responsibility.
Design
Editorial
Authors
Discussion
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Member takes
Implication
This commentary highlights the need for transparency, provenance, and enforceable human responsibility to mitigate the risks of AI in biomedical publishing.
Key Points
- This commentary examines AI's evolving role in biomedical publishing and its implications.
- Discusses the integration of AI in research and publishing workflows
- Reviews benefits and limitations of generative models and machine learning
- Highlights risks associated with AI, including bias and transparency issues.
- Identified risks like fabricated content and biased outputs that threaten scientific trust
- Proposed emphasis on transparency and accountability to guide AI usage
- Outlined practical expectations for authors, reviewers, and publishers regarding reporting standards.
Cite This Study
Guzik et al. (2026) reported an editorial. Artificial intelligence in biomedical publishing offers opportunities to accelerate knowledge generation but introduces risks requiring transparency, provenance, and enforceable human responsibility.