Navigating academic integrity in biomedical research: the impact of large language models on current practices and future directions
Year: 2025
Type: article
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.
Source: International Journal of Surgery
Authors: Anqi Lin, Zuwei Chen, Aimin Jiang, Bufu Tang, Chang Qi, Lingxuan Zhu, Weiming Mou, Wenyi Gan, Dongqiang Zeng, Mingjia Xiao, Guangdi Chu, Shengkun Peng, Hank Z.H. Wong, Lin Zhang, Hengguo Zhang, Xinpei Deng, Quan Cheng, Jian Zhang, Peng Luo
Institutions: Zhujiang Hospital, Kangda College of Nanjing Medical University, Southern Medical University, Second Military Medical University, Changhai Hospital, Fudan University, Zhongshan Hospital, TU Wien, Shanghai Jiao Tong University, Shanghai First People's Hospital, Jinan University, Zhuhai People's Hospital, Nanfang Hospital, South China University of Technology, Wenzhou Medical University, Quzhou City People's Hospital, Affiliated Hospital of Qingdao University, University of Electronic Science and Technology of China, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Hong Kong, Monash University, Anhui Medical University, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Central South University, Xiangya Hospital Central South University
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,450
OpenAlex ID: W4417229770