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

Authors :
Li C
Zhang XY
Wu YH
Yang XL
Yu HR
Jin HB
Li YB
Zhu ZH
Liu R
Liu N
Xie Y
Lyu LL
Zhu XH
Tang H
Li HF
Li HL
Zeng XJ
Chen ZX
Fan XF
Wang Y
Wu ZJ
Wu ZQ
Guan YQ
Xue MM
Luo B
Wang AM
Yang XW
Ying Y
Yang XH
Huang XZ
Lang MF
Chen SM
Zhang HH
Zhang Z
Huang W
Xu GB
Liu JQ
Song T
Xiao J
Xia YL
Guan YF
Zhu L
Source :
Sheng li xue bao : [Acta physiologica Sinica] [Sheng Li Xue Bao] 2024 Dec 25; Vol. 76 (6), pp. 937-942.
Publication Year :
2024

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.

Details

Language :
Chinese
ISSN :
0371-0874
Volume :
76
Issue :
6
Database :
MEDLINE
Journal :
Sheng li xue bao : [Acta physiologica Sinica]
Publication Type :
Academic Journal
Accession number :
39780570