Big Medical Data and Medical AI Standards: Status Quo, Opportunities and Challenges
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摘要: 医学大数据和人工智能(artificial intelligence，AI)在提升医学资源利用率和服务质量方面具有极大的潜力，但同时也在隐私保护和技术风险方面带来挑战。标准是构造、评价和应用新技术的共识和规范，医学大数据和AI在临床的应用迫切需要制订数据、系统、计量标准以及应用和评价新技术的行为规范。本文定义了医学大数据与AI标准的内涵，包括数据相关标准、公共数据集、测试基准、行为规范；总结了医学大数据和AI标准的现状、潜在问题及挑战；在展望医学大数据与AI发展前景的同时，提出了结合大数据/AI增强的系统和医学科学大装置的系统新架构。Abstract: Big medical data and medical artificial intelligence (AI) not only have the great potential for improving the utilization of medical resources and the quality of medical service, but also pose challenges to privacy protection and technical risks. Standards are the consensus and norms for constructing, evaluating, and applying new technologies. The clinical application of big medical data and medical AI urgently needs regulations on data, systems, measurement standards, and codes of practice for evaluating new technologies. This paper defines big medical data and medical AI standards, including data-related standards, public datasets, benchmarks, codes of practice, and summarizes state-of-the-art and state-of-the-practice of big medical data and medical AI standards. While looking forward to the development prospect of big medical data and medical AI, we propose an innovative architecture consisting of big-data-and-AI-enhanced medical information systems and the big medical science infrastructure.
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Key words:
- big medical data /
- medical artificial intelligence /
- standards /
- benchmarks /
- codes of practice
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