人工智能-ML 的监管问题。

IF 7.1 1区 医学 Q1 PATHOLOGY Modern Pathology Pub Date : 2024-09-12 DOI:10.1016/j.modpat.2024.100609
Liron Pantanowitz , Matthew Hanna , Joshua Pantanowitz , Joe Lennerz , Walter H. Henricks , Peter Shen , Bruce Quinn , Shannon Bennet , Hooman H. Rashidi
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引用次数: 0

摘要

在医疗保健领域,已经开发和部署了大量生成式和非生成式人工智能和机器学习(AI-ML)工具。与此同时,医疗设备制造商也在利用 AI-ML。然而,在医疗保健领域采用人工智能会引发一些问题,包括安全、安保、道德偏见、问责、信任、经济影响和环境影响。有效的监管可以降低其中一些风险,促进公平,建立标准,并倡导更可持续的人工智能实践。对人工智能工具进行监管不仅能确保其安全有效地应用,还能促进公众信任。重要的是,监管应保持灵活性,以适应该领域的快速发展,从而支持创新,同时也不给我们现有的一些完善框架增加额外负担。本文涉及人工智能医疗的地区和全球监管方面,包括数据隐私、软件即医疗设备(SaMD)、机构审批和许可途径、报销和实验室开发测试(LDTs)。
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Regulatory Aspects of Artificial Intelligence and Machine Learning
In the realm of health care, numerous generative and nongenerative artificial intelligence and machine learning (AI-ML) tools have been developed and deployed. Simultaneously, manufacturers of medical devices are leveraging AI-ML. However, the adoption of AI in health care raises several concerns, including safety, security, ethical biases, accountability, trust, economic impact, and environmental effects. Effective regulation can mitigate some of these risks, promote fairness, establish standards, and advocate for more sustainable AI practices. Regulating AI tools not only ensures their safe and effective adoption but also fosters public trust. It is important that regulations remain flexible to accommodate rapid advances in this field to support innovation and also not to add additional burden to some of our preexisting and well-established frameworks. This study covers regional and global regulatory aspects of AI-ML including data privacy, software as a medical device, agency approval and clearance pathways, reimbursement, and laboratory-developed tests.
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来源期刊
Modern Pathology
Modern Pathology 医学-病理学
CiteScore
14.30
自引率
2.70%
发文量
174
审稿时长
18 days
期刊介绍: Modern Pathology, an international journal under the ownership of The United States & Canadian Academy of Pathology (USCAP), serves as an authoritative platform for publishing top-tier clinical and translational research studies in pathology. Original manuscripts are the primary focus of Modern Pathology, complemented by impactful editorials, reviews, and practice guidelines covering all facets of precision diagnostics in human pathology. The journal's scope includes advancements in molecular diagnostics and genomic classifications of diseases, breakthroughs in immune-oncology, computational science, applied bioinformatics, and digital pathology.
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