[Expert consensus on ethical requirements for artificial intelligence (AI) processing medical data].

Journal: Sheng li xue bao : [Acta physiologica Sinica]
PMID: 39780570

Abstract

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.

Authors

  • Cong Li
    Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry and Materials Science, National Demonstration Center for Experimental Chemistry Education, Northwest University, Xi'an, Shaanxi 710127, China. Electronic address: licong@nwu.edu.cn.
  • Xiao-Yan Zhang
    Department of Dermatology, Department of Ultrasound, General Hospital of Beijing Military Command, Beijing, China.
  • Yun-Hong Wu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Xiao-Lei Yang
    Dalian Medical University, Dalian 116041, China.
  • Hua-Rong Yu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Hong-Bo Jin
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Ying-Bo Li
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Zhao-Hui Zhu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Rui Liu
    School of Education, China West Normal University, Nanchong, Sichuan, China.
  • Na Liu
  • Yi Xie
    Department of Plastic Surgery Peninsula Health Melbourne Victoria Australia.
  • Lin-Li Lyu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Xin-Hong Zhu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Hong Tang
    Department of Orthopedics, Orthopedic Center of Chinese PLA, Southwest Hospital, Third Military Medical University, Chongqing, 400038, P.R.China.
  • Hong-Fang Li
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Hong-Li Li
    College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China; School of Mathematics, Southeast University, Nanjing 210096, China. Electronic address: lihongli@xju.edu.cn.
  • Xiang-Jun Zeng
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Zai-Xing Chen
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Xiao-Fang Fan
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Zhi-Juan Wu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Zun-Qiu Wu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Ya-Qun Guan
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Ming-Ming Xue
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Bin Luo
  • Ai-Mei Wang
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Xin-Wang Yang
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Ying Ying
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Xiu-Hong Yang
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Xin-Zhong Huang
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Ming-Fei Lang
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Shi-Min Chen
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Huan-Huan Zhang
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Zhong Zhang
    School of Mechanical and Aerospace Engineering, Jilin University, Changchun, China.
  • Wu Huang
    School of Business Administration, Zhongnan University of Economics and Law, Wuhan, Hubei, China.
  • Guo-Biao Xu
    Virtual Simulation and Artificial Intelligence Committee, Chinese Association for Physiological Sciences.
  • Jia-Qi Liu
    Huawei Technologies Co., Ltd., Shenzhen 518000, China.
  • Tao Song
    Department of Cleft Lip and Palate, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing.
  • Jing Xiao
    Xiyuan Hospital, China Academy of Chinese Medical Sciences(CACMS), Beijing, China.
  • Yun-Long Xia
    Dalian Medical University, Dalian 116041, China.
  • You-Fei Guan
    Dalian Medical University, Dalian 116041, China.
  • Liang Zhu
    SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao 266104, China.

Keywords

External Resources

Popular Topics
Recent Journals