Application Progress of Generative Artificial Intelligence in Medical Research Management

Corresponding author: bai huijun, camsacc@cams.cn

DOI: 10.12201/bmr.202610.00048

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  Abstract: 〔Abstract〕Purpose/Significance: To systematically review the technological evolution and application of generative AI in medical research management, analyzing its progress and challenges in data governance, process optimization, and decision support to provide references for its application. Method/Process: A systematic literature review was conducted across technological evolution, management processes, data governance and privacy protection, and decision credibility, with three typical cases analyzed for their technical pathways and governance practices. Result/Conclusion: Generative artificial intelligence has demonstrated practical value in scenarios such as textual parsing for research administration, grant funding data analysis, and workflow automation. Retrieval-augmented generation, knowledge graphs, and human-AI collaboration mechanisms help improve the traceability and reliability of outputs. Nevertheless, challenges remain, including model hallucinations, inconsistent cross-institutional data standards, high deployment costs, and ambiguous accountability frameworks. It is recommended that industry authorities, research institutions, and technical support departments collaboratively advance semantic governance, tiered risk management, and application evaluation. Efforts should be accelerated to develop data terminology standards, implement concept mapping, and enforce semantic governance of business rules, clarify the division of responsibilities between humans and AI, and strengthen AI literacy training for professionals.

  Key words: Generative artificial intelligence; Medical research management; Large language model; Data governance; Research management informatization

  Submit time: 21 October 2026

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  1	2026-06-23	10.12201/bmr.202610.00048V1	Download

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