Using AI to improve peer review and research integrity in scientific journals

Area of Science:

• Biomedical Sciences
• Scientific Publishing
• Research Integrity

Background:

• Traditional peer review is increasingly inefficient, biased, and ineffective.
• Maintaining research integrity is crucial, especially with declining public trust in science.
• The sheer volume of over 3 million biomedical manuscripts annually overwhelms manual review processes.

Purpose of the Study:

• To highlight the limitations of current peer review systems.
• To emphasize the need for novel approaches to ensure scientific integrity.
• To introduce artificial intelligence (AI) as a tool to augment editorial and peer review.

Main Methods:

• Analysis of the current state of scientific publishing and peer review.
• Identification of challenges in maintaining research integrity.
• Exploration of AI as a supplementary tool for manuscript evaluation.

Main Results:

• Current peer review methods are insufficient to guarantee the integrity of the rapidly growing body of scientific literature.
• Human editorial and peer review alone cannot cope with the scale of biomedical publications.
• AI presents a viable option to assist in the editorial and peer review process.

Conclusions:

• New strategies are essential to uphold research integrity.
• Artificial intelligence can play a significant role in improving the efficiency and effectiveness of peer review.
• Integrating AI is necessary to manage the increasing volume of scientific publications and maintain public trust in science.