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Cited by 2Academic integrity and plagiarismEthics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Navigating academic integrity in biomedical research: The impact of large language models on current practices and future directions

Open access
Lin, Anqi, Chen, Zuwei, Jiang, Aimin, Tang, Bufu, Qi, Chang, Zhu, Lingxuan, Mou, Weiming, Gan, Wenyi +11 more·2026·International Journal of Surgery
DOI 10.1097/js9.0000000000003839
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Abstract

As large language models (LLMs) continue to advance, they have garnered widespread public attention and extensive application across numerous industries and academic disciplines. The proliferation of LLMs has sparked considerable research interest, with studies primarily focusing on their technical characteristics and specific application scenarios. However, systematic research examining the impact of LLMs on academic integrity remains relatively scarce. Academic integrity is of paramount importance in the biomedical field. Therefore, this paper aims to examine both the opportunities and challenges that LLMs present to academic integrity in the biomedical field, and proposes solutions for optimizing the beneficial applications of LLMs. From a positive perspective, LLMs offer substantial benefits to researchers by enhancing research efficiency, improving research quality, and facilitating the generation and dissemination of academic insights. However, they also present numerous challenges, including the potential for promoting academic misconduct, generating content inaccuracies or ambiguous expressions, introducing bias and fairness concerns, compromising peer review mechanisms, facilitating the dissemination of misinformation, and undermining higher education - all of which demand careful attention. To address these issues, we propose solutions and feasible strategies centered on ten core dimensions: establishing policies and regulatory guidelines, enhancing AI literacy and application capabilities, developing and improving relevant technical tools, establishing human-AI collaboration models, reforming peer review procedures and academic evaluation systems, promoting international cooperation and standardization, increasing transparency and strengthening disclosure, reinforcing professional ethics education, and advancing artificial intelligence detection technologies. Overall, while LLMs undoubtedly pose challenges for maintaining academic integrity, their potential for positive impact remains promising. It is anticipated that with technological advancement and improved ethical standards, LLMs will ultimately preserve and strengthen academic integrity.

Integrity signals

Registry

Crossref · 10.1097/js9.0000000000003839

Cites

93 of 93 references verified0 citation errors · 0 not checkable

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  • The integration of AI technologies may be associated with more difficult-to-detect forms of misconduct, such as AIGC misuse and hallucinated findings.

    “In addition, the integration of AI technologies may be associated with more difficult-to-detect forms of misconduct, such as AIGC misuse and hallucinated findings (Lin et al., 2026).”

    From The Attention Mismatch: Mapping the Structural Academic Governance Deficit in the Age of Generative AI (2026) · cites this paper as Lin et al., 2026

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Authors
Lin, A., Chen, Z., Jiang, A., Tang, B., Qi, C., Zhu, L., Mou, W., Gan, W., Zeng, D., Xiao, M., Chu, G., Peng, S., Wong, H. Z. H., Zhang, L., Zhang, H., Deng, X., Cheng, Q., Zhang, J., & Luo, P.
Affiliations
  • Zhujiang Hospital (CN)
  • Second Military Medical University (CN)
  • Fudan University (CN)
  • TU Wien (AT)
  • Shanghai Jiao Tong University (CN)
  • Jinan University (CN)
  • Nanfang Hospital (CN)
  • Wenzhou Medical University (CN)
  • Affiliated Hospital of Qingdao University (CN)
  • University of Electronic Science and Technology of China (CN)
  • University of Hong Kong (HK)
  • Monash University (AU)
  • Anhui Medical University (CN)
  • Sun Yat-sen University Cancer Center (CN)
  • Central South University (CN)
Corresponding author
  • Zhang, Jian
  • Luo, Peng
ORCID
Venue
International Journal of Surgery
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2025-11-21
Volume
112
Issue
2
Pages
4418-4433
ISSN
1743-9159 (ISSN-L)
DOI
10.1097/js9.0000000000003839
OpenAlex
W4417229770
Cited by
2
References
93
Citations by year
2026: 2
FWCI
0.31
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Surgery (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Safety Research › Academic integrity and plagiarism
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
large language models, academic integrity, biomedical research, academic misconduct, peer review, misinformation, AI literacy, human-AI collaboration, AI detection, research ethics, AI regulation, bias and fairness
MeSH terms
Large Language Models, Humans, Language, Scientific Misconduct, Biomedical Research

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