Governance and management for promoting science and techonolgy in medicine by digital and artificial intelligence
10.3760/cma.j.cn113565-20250119-00014
- VernacularTitle:数智赋能医学科技的治理管理
- Author:
Jian GUAN
1
Author Information
1. 北京协和医学院&中国医学科学院 北京协和医院 国家人口健康科学数据中心（临床医学），北京 100730
- Publication Type:Journal Article
- Keywords:
Big data;
Artificial intelligence;
Medical research;
Algorithms;
Generative AI;
Data governance;
Data management;
Data ethics;
Intelligence property;
Resolutio
- From:
Chinese Journal of Medical Science Research Management
2025;38(1):1-7
- CountryChina
- Language:Chinese
-
Abstract:
Objective:This study aimed to explore the challenges and issues arising from the factors that affect the governance and management of big data and artificial intelligence in medicine, and to establish a foundation for proposing solutions to these challenges and issues.Methods:We analyzed how big data and artificial intelligence influence different aspects of medical research by reviewing a range of literature. We proposed potential strategies to address the major challenges and issues associated with medical big data and artificial intelligence by analyzing their core elements and interrelationships.Results:The application of big data and artificial intelligence has significantly impacted the paradigms of medical research, drug development, clinical decision-making, and medical education. Two main aspects highlighted the challenges and issues related to governance and management arising from these advancements. The first involved ethical challenges stemming from data and algorithmic processes, including those related to artificial intelligence. A major concern was the potential bias in the algorithms, which can emerge during data collection, coding, and feedback. The second aspect focused on the governance and management elements of the data and stakeholders. Two key issues were the quality and integration efficiency of fundamental data, as well as property rights and intellectual property related to data, which currently lack a proper recognition system. This recognition was vital for distributing rights, interests, and responsibilities among stakeholders during data sharing and applications.Conclusion:Key issues regarding the governance and management of big data and artificial intelligence in medicine should be addressed. These include developing a framework for data ethics, including ethical review strategies and keypoints for medical artificial intelligence; establishing standards for data structure to enhance data quality and interactivity; and clarifying the principles of decisions on data ownership and intellectual property to distribute rights and interests.
