Reconstruction of scientific ethics and norms for the medical use of artificial intelligence tools

With the rapid development of artificial intelligence, AI tools have demonstrated significant value in medical research and academic writing, enhancing efficiency in data processing, literature retrieval, manuscript drafting, visualization, and interdisciplinary collaboration. Beyond serving as auxiliary tools, AI is increasingly becoming a research partner, contributing to hypothesis generation, experimental design, and multimodal data analysis, thereby fostering a paradigm shift toward“ human–AI coresearch”. Typical applications include rapid drafting of medical manuscripts, research integrity checks, and automated generation of imaging reports and scientific figures. However, the widespread adoption of AI also raises challenges concerning authorship, data traceability, content reliability, and privacy protection. International guidelines such as the ICMJE Recommendations and public statements from Science and Nature explicitly emphasize that AI tools cannot be listed as authors, that their use must be transparently disclosed, and that ultimate responsibility lies with human researchers. Therefore, it is urgent to establish a normative framework centered on transparency, accountability, verifiability, and compliant openness, ensuring that AI delivers both efficiency and innovation while laying the foundation for a sustainable research ecosystem in the digital era.

Key Words: artificial intelligence; medical research paradigm; data-driven science; generative models; research ethics