中国人工智能医疗器械软件的监管框架:中国人工智能医疗器械软件监管框架:比较分析及对全球制造商的影响评述》。

JMIR AI Pub Date : 2024-07-29 DOI:10.2196/46871
Yu Han, Aaron Ceross, Jeroen Bergmann
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引用次数: 0

摘要

中国国务院发布了《新一代人工智能(AI)发展规划》,概述了中国到 2030 年在人工智能领域占据全球领先地位的雄心壮志。这一举措强调了人工智能在制造、法律和医疗等不同领域的广泛适用性。随着中国成为医疗设备的主要生产国和消费国,软件注册量也显著增加。本研究旨在研究中国医疗相关软件开发的扩散情况。本研究概述了中国的医疗器械软件监管框架。分析涵盖了作为医疗器械的软件和医疗器械中的软件。研究采用比较的方法,考察了中国、美国和欧洲对人工智能和机器学习医疗器械的监管情况。研究强调了中国医疗保健相关软件开发的显著激增,这导致对全面监管指导的需求增加,尤其是对国际制造商而言。比较分析揭示了三个地区不同的监管框架和要求。本文对中国医疗软件的监管现状进行了有益的概述,并指出了人工智能和机器学习技术的快速发展所带来的监管挑战。了解这些挑战对于国际制造商和利益相关者驾驭复杂的监管环境至关重要。
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Regulatory Frameworks for AI-Enabled Medical Device Software in China: Comparative Analysis and Review of Implications for Global Manufacturer.

The China State Council released the new generation artificial intelligence (AI) development plan, outlining China's ambitious aspiration to assume global leadership in AI by the year 2030. This initiative underscores the extensive applicability of AI across diverse domains, including manufacturing, law, and medicine. With China establishing itself as a major producer and consumer of medical devices, there has been a notable increase in software registrations. This study aims to study the proliferation of health care-related software development within China. This work presents an overview of the Chinese regulatory framework for medical device software. The analysis covers both software as a medical device and software in a medical device. A comparative approach is employed to examine the regulations governing medical devices with AI and machine learning in China, the United States, and Europe. The study highlights the significant proliferation of health care-related software development within China, which has led to an increased demand for comprehensive regulatory guidance, particularly for international manufacturers. The comparative analysis reveals distinct regulatory frameworks and requirements across the three regions. This paper provides a useful outline of the current state of regulations for medical software in China and identifies the regulatory challenges posed by the rapid advancements in AI and machine learning technologies. Understanding these challenges is crucial for international manufacturers and stakeholders aiming to navigate the complex regulatory landscape.

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