ReviewJournal of Korean medical science2025
Artificial Intelligence in Peer Review: Enhancing Efficiency While Preserving Integrity.
Review in Journal of Korean medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Is AI Redefining Scientific Publications?Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Article
- Alternative quadruplex real-time PCR reactions for detection and discrimination ofMicrobiology spectrum · 2026Article
- AI hallucinations in academic writing: implications for research integrity.Naunyn-Schmiedeberg's archives of pharmacology · 2026Review
- The paradox of peer review: protecting science or policing thought?Internal medicine journal · 2026Article
- Behavior characteristics of peer reviewers in medical journals: a survey from China.Research integrity and peer review · 2026Article
- Evaluating Large Language Models for Post-Publication Promotion: A Blinded Comparative Study of Social Media Posts in Public Health.Journal of Korean medical science · 2026Article
- Artificial Intelligence in Scientific Judgment: Assistance, Dependence, or Disruption?Pakistan journal of medical sciences · 2026Article
- Prompt injection in manuscripts: exploiting loopholes or crossing ethical lines?Research integrity and peer review · 2026Article
- Expert assignment system based on natural language processing for Marie Sklodowska-Curie actions.Scientific reports · 2026Article
- ChatGPT-4.0 as a Tool for Automated Review of Ethics and Transparency in Biomedical Literature.Journal of Korean medical science · 2026Article
- Invisible Text Injection and Peer Review by AI Models.JAMA network open · 2026Article
- Use of artificial intelligence tools in the publishing process: expectations from publishers through author guidelines.Frontiers in research metrics and analytics · 2026Article
- Impact of an AI workshop on knowledge and attitudes toward AI in scientific publishing among surgeons at an international abdominal wall surgery congress.Journal of abdominal wall surgery : JAWS · 2026Article
- Artificial Intelligence in Detecting Statistical Errors: Implications for Authors, Reviewers, and Editors.Journal of Korean medical science · 2025Review
- Analysis of Retracted Publications on Artificial Intelligence: Trends, Ethical Concerns, and Scientific Integrity.Journal of Korean medical science · 2025Article
- Challenges, Ethical Considerations, and Best Practices of Using AI-Assisted Translation in Medical Writing: Examples From Japanese-English Translations.Journal of Korean medical science · 2025Article
- Review
- Artificial Intelligence in Peer Review: Ethical Risks and Practical Limits.Turkish archives of otorhinolaryngology · 2025Article
- Perspectives of Artificial Intelligence Use for In-House Ethics Checks of Journal Submissions.Journal of Korean medical science · 2025Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid advancement of artificial intelligence (AI) has transformed various aspects of scientific research, including academic publishing and peer review. In recent years, AI tools such as large language models have demonstrated their capability to streamline numerous tasks traditionally handled by human editors and reviewers. These applications range from automated language and grammar checks to plagiarism detection, format compliance, and even preliminary assessment of research significance. While AI substantially benefits the efficiency and accuracy of academic processes, its integration raises critical ethical and methodological questions, particularly in peer review. AI lacks the subtle understanding of complex scientific content that human expertise provides, posing challenges in evaluating research novelty and significance. Additionally, there are risks associated with over-reliance on AI, potential biases in AI algorithms, and ethical concerns related to transparency, accountability, and data privacy. This review evaluates the perspectives within the scientific community on integrating AI in peer review and academic publishing. By exploring both AI's potential benefits and limitations, we aim to offer practical recommendations that ensure AI is used as a supportive tool, supporting but not replacing human expertise. Such guidelines are essential for preserving the integrity and quality of academic work while benefiting from AI's efficiencies in editorial processes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.